[{"title":"VoRF: Volumetric Relightable Faces","article_processing_charge":"No","abstract":[{"text":"Portrait viewpoint and illumination editing is an important problem with several applications in VR/AR, movies, and photography. Comprehensive knowledge of geometry and illumination is critical for obtaining photorealistic results. Current methods are unable to explicitly model in 3D while handing both viewpoint and illumination editing from a single image. In this paper, we propose VoRF, a novel approach that can take even a single portrait image as input and relight human heads under novel illuminations that can be viewed from arbitrary viewpoints. VoRF represents a human head as a continuous volumetric field and learns a prior model of human heads using a coordinate-based MLP with separate latent spaces for identity and illumination. The prior model is learnt in an auto-decoder manner over a diverse class of head shapes and appearances, allowing VoRF to generalize to novel test identities from a single input image. Additionally, VoRF has a reflectance MLP that uses the intermediate features of the prior model for rendering One-Light-at-A-Time (OLAT) images under novel views. We synthesize novel illuminations by combining these OLAT images with target environment maps. Qualitative and quantitative evaluations demonstrate the effectiveness of VoRF for relighting and novel view synthesis even when applied to unseen subjects under uncontrolled illuminations.","lang":"eng"}],"publication_status":"published","author":[{"full_name":"Rao, Pramod","last_name":"Rao","first_name":"Pramod"},{"first_name":"Mallikarjun","last_name":"B R","full_name":"B R, Mallikarjun"},{"last_name":"Fox","first_name":"Gereon","full_name":"Fox, Gereon"},{"full_name":"Weyrich, Tim","first_name":"Tim","last_name":"Weyrich"},{"last_name":"Bickel","first_name":"Bernd","orcid":"0000-0001-6511-9385","id":"49876194-F248-11E8-B48F-1D18A9856A87","full_name":"Bickel, Bernd"},{"full_name":"Seidel, Hans-Peter","first_name":"Hans-Peter","last_name":"Seidel"},{"first_name":"Hanspeter","last_name":"Pfister","full_name":"Pfister, Hanspeter"},{"full_name":"Matusik, Wojciech","first_name":"Wojciech","last_name":"Matusik"},{"full_name":"Tewari, Ayush","first_name":"Ayush","last_name":"Tewari"},{"last_name":"Theobalt","first_name":"Christian","full_name":"Theobalt, Christian"},{"full_name":"Elgharib, Mohamed","first_name":"Mohamed","last_name":"Elgharib"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","has_accepted_license":"1","main_file_link":[{"url":"https://bmvc2022.mpi-inf.mpg.de/708/","open_access":"1"}],"ddc":["000"],"conference":{"location":"London, United Kingdom","end_date":"2022-11-24","name":"BMVC: British Machine Vision Conference","start_date":"2022-11-21"},"file":[{"access_level":"open_access","title":"VoRF: Volumetric Relightable Faces","relation":"main_file","checksum":"b60b70bb48700aee709c85a69231821d","file_size":5202710,"date_updated":"2023-01-30T10:48:18Z","file_id":"12453","creator":"bbickel","date_created":"2023-01-30T10:48:18Z","file_name":"vorf_main.pdf","content_type":"application/pdf"},{"content_type":"application/pdf","file_name":"vorf_supp.pdf","date_created":"2023-01-30T10:48:29Z","creator":"bbickel","file_id":"12454","date_updated":"2023-01-30T10:48:29Z","file_size":37953188,"title":"VoRF: Volumetric Relightable Faces – SUPPLEMENTAL MATERIAL –","access_level":"open_access","relation":"supplementary_material","checksum":"ce5f4ce66eaaa1590ee5df989fca6f61"},{"access_level":"open_access","relation":"supplementary_material","checksum":"08aecca434b08fee75ee1efe87943718","date_updated":"2023-01-30T10:48:37Z","file_size":57855492,"file_id":"12455","creator":"bbickel","date_created":"2023-01-30T10:48:37Z","content_type":"video/mp4","file_name":"video.mp4"}],"quality_controlled":"1","publication":"33rd British Machine Vision Conference","year":"2022","date_created":"2023-01-30T10:47:06Z","article_number":"708","language":[{"iso":"eng"}],"month":"12","date_published":"2022-12-01T00:00:00Z","department":[{"_id":"BeBi"}],"publisher":"British Machine Vision Association and Society for Pattern Recognition","date_updated":"2023-10-31T08:40:55Z","oa":1,"file_date_updated":"2023-01-30T10:48:37Z","_id":"12452","scopus_import":"1","oa_version":"Published Version","acknowledgement":"This work was supported by the ERC Consolidator Grant 4DReply (770784).","type":"conference","citation":{"apa":"Rao, P., B R, M., Fox, G., Weyrich, T., Bickel, B., Seidel, H.-P., … Elgharib, M. (2022). VoRF: Volumetric Relightable Faces. In <i>33rd British Machine Vision Conference</i>. London, United Kingdom: British Machine Vision Association and Society for Pattern Recognition.","chicago":"Rao, Pramod, Mallikarjun B R, Gereon Fox, Tim Weyrich, Bernd Bickel, Hans-Peter Seidel, Hanspeter Pfister, et al. “VoRF: Volumetric Relightable Faces.” In <i>33rd British Machine Vision Conference</i>. British Machine Vision Association and Society for Pattern Recognition, 2022.","mla":"Rao, Pramod, et al. “VoRF: Volumetric Relightable Faces.” <i>33rd British Machine Vision Conference</i>, 708, British Machine Vision Association and Society for Pattern Recognition, 2022.","short":"P. Rao, M. B R, G. Fox, T. Weyrich, B. Bickel, H.-P. Seidel, H. Pfister, W. Matusik, A. Tewari, C. Theobalt, M. Elgharib, in:, 33rd British Machine Vision Conference, British Machine Vision Association and Society for Pattern Recognition, 2022.","ieee":"P. Rao <i>et al.</i>, “VoRF: Volumetric Relightable Faces,” in <i>33rd British Machine Vision Conference</i>, London, United Kingdom, 2022.","ama":"Rao P, B R M, Fox G, et al. VoRF: Volumetric Relightable Faces. In: <i>33rd British Machine Vision Conference</i>. British Machine Vision Association and Society for Pattern Recognition; 2022.","ista":"Rao P, B R M, Fox G, Weyrich T, Bickel B, Seidel H-P, Pfister H, Matusik W, Tewari A, Theobalt C, Elgharib M. 2022. VoRF: Volumetric Relightable Faces. 33rd British Machine Vision Conference. BMVC: British Machine Vision Conference, 708."},"status":"public","day":"01"},{"author":[{"full_name":"Mondelli, Marco","id":"27EB676C-8706-11E9-9510-7717E6697425","orcid":"0000-0002-3242-7020","first_name":"Marco","last_name":"Mondelli"},{"last_name":"Venkataramanan","first_name":"Ramji","full_name":"Venkataramanan, Ramji"}],"user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","volume":2022,"related_material":{"record":[{"relation":"earlier_version","id":"10598","status":"public"}]},"article_processing_charge":"Yes (via OA deal)","abstract":[{"text":"We consider the problem of estimating a signal from measurements obtained via a generalized linear model. We focus on estimators based on approximate message passing (AMP), a family of iterative algorithms with many appealing features: the performance of AMP in the high-dimensional limit can be succinctly characterized under suitable model assumptions; AMP can also be tailored to the empirical distribution of the signal entries, and for a wide class of estimation problems, AMP is conjectured to be optimal among all polynomial-time algorithms. However, a major issue of AMP is that in many models (such as phase retrieval), it requires an initialization correlated with the ground-truth signal and independent from the measurement matrix. Assuming that such an initialization is available is typically not realistic. In this paper, we solve this problem by proposing an AMP algorithm initialized with a spectral estimator. With such an initialization, the standard AMP analysis fails since the spectral estimator depends in a complicated way on the design matrix. Our main contribution is a rigorous characterization of the performance of AMP with spectral initialization in the high-dimensional limit. The key technical idea is to define and analyze a two-phase artificial AMP algorithm that first produces the spectral estimator, and then closely approximates the iterates of the true AMP. We also provide numerical results that demonstrate the validity of the proposed approach.","lang":"eng"}],"publication_status":"published","external_id":{"isi":["000889589900001"]},"title":"Approximate message passing with spectral initialization for generalized linear models","keyword":["Statistics","Probability and Uncertainty","Statistics and Probability","Statistical and Nonlinear Physics"],"year":"2022","date_created":"2023-02-02T08:31:57Z","article_number":"114003","issue":"11","publication_identifier":{"issn":["1742-5468"]},"doi":"10.1088/1742-5468/ac9828","publication":"Journal of Statistical Mechanics: Theory and Experiment","corr_author":"1","file":[{"success":1,"creator":"dernst","date_created":"2023-02-02T08:35:52Z","content_type":"application/pdf","file_name":"2022_JourStatisticalMechanics_Mondelli.pdf","access_level":"open_access","checksum":"01411ffa76d3e380a0446baeb89b1ef7","relation":"main_file","date_updated":"2023-02-02T08:35:52Z","file_size":1729997,"file_id":"12481"}],"quality_controlled":"1","has_accepted_license":"1","ddc":["510","530"],"article_type":"original","intvolume":"      2022","oa_version":"Published Version","type":"journal_article","acknowledgement":"The authors would like to thank Andrea Montanari for helpful discussions.\r\nM Mondelli was partially supported by the 2019 Lopez-Loreta Prize. R Venkataramanan was partially supported by the Alan Turing Institute under the EPSRC Grant\r\nEP/N510129/1.","_id":"12480","scopus_import":"1","isi":1,"oa":1,"file_date_updated":"2023-02-02T08:35:52Z","month":"11","language":[{"iso":"eng"}],"date_published":"2022-11-24T00:00:00Z","department":[{"_id":"MaMo"}],"publisher":"IOP Publishing","date_updated":"2025-04-15T07:50:16Z","tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)"},"day":"24","status":"public","citation":{"ista":"Mondelli M, Venkataramanan R. 2022. Approximate message passing with spectral initialization for generalized linear models. Journal of Statistical Mechanics: Theory and Experiment. 2022(11), 114003.","ama":"Mondelli M, Venkataramanan R. Approximate message passing with spectral initialization for generalized linear models. <i>Journal of Statistical Mechanics: Theory and Experiment</i>. 2022;2022(11). doi:<a href=\"https://doi.org/10.1088/1742-5468/ac9828\">10.1088/1742-5468/ac9828</a>","short":"M. Mondelli, R. Venkataramanan, Journal of Statistical Mechanics: Theory and Experiment 2022 (2022).","ieee":"M. Mondelli and R. Venkataramanan, “Approximate message passing with spectral initialization for generalized linear models,” <i>Journal of Statistical Mechanics: Theory and Experiment</i>, vol. 2022, no. 11. IOP Publishing, 2022.","mla":"Mondelli, Marco, and Ramji Venkataramanan. “Approximate Message Passing with Spectral Initialization for Generalized Linear Models.” <i>Journal of Statistical Mechanics: Theory and Experiment</i>, vol. 2022, no. 11, 114003, IOP Publishing, 2022, doi:<a href=\"https://doi.org/10.1088/1742-5468/ac9828\">10.1088/1742-5468/ac9828</a>.","apa":"Mondelli, M., &#38; Venkataramanan, R. (2022). Approximate message passing with spectral initialization for generalized linear models. <i>Journal of Statistical Mechanics: Theory and Experiment</i>. IOP Publishing. <a href=\"https://doi.org/10.1088/1742-5468/ac9828\">https://doi.org/10.1088/1742-5468/ac9828</a>","chicago":"Mondelli, Marco, and Ramji Venkataramanan. “Approximate Message Passing with Spectral Initialization for Generalized Linear Models.” <i>Journal of Statistical Mechanics: Theory and Experiment</i>. IOP Publishing, 2022. <a href=\"https://doi.org/10.1088/1742-5468/ac9828\">https://doi.org/10.1088/1742-5468/ac9828</a>."},"project":[{"name":"Prix Lopez-Loretta 2019 - Marco Mondelli","_id":"059876FA-7A3F-11EA-A408-12923DDC885E"}]},{"file_date_updated":"2023-02-23T10:30:04Z","oa":1,"date_updated":"2025-12-30T11:04:31Z","arxiv":1,"publisher":"ML Research Press","department":[{"_id":"ChLa"}],"date_published":"2022-12-22T00:00:00Z","language":[{"iso":"eng"}],"month":"12","acknowledgement":"The authors would like to thank Bernd Prach, Elias Frantar, Alexandra Peste, Mahdi Nikdan, and Peter Súkeník for their helpful feedback. This research was supported by the Scientific Service Units (SSU) of IST Austria through resources provided by Scientific Computing (SciComp). This publication was made possible by an ETH AI Center postdoctoral fellowship granted to Nikola Konstantinov. Eugenia Iofinova was supported in part by the FWF DK VGSCO, grant agreement number W1260-N35. ","type":"journal_article","oa_version":"Published Version","article_type":"original","_id":"12495","project":[{"grant_number":"W1260-N35","_id":"9B9290DE-BA93-11EA-9121-9846C619BF3A","name":"Vienna Graduate School on Computational Optimization"}],"citation":{"apa":"Iofinova, E. B., Konstantinov, N. H., &#38; Lampert, C. (2022). FLEA: Provably robust fair multisource learning from unreliable training data. <i>Transactions on Machine Learning Research</i>. ML Research Press.","chicago":"Iofinova, Eugenia B, Nikola H Konstantinov, and Christoph Lampert. “FLEA: Provably Robust Fair Multisource Learning from Unreliable Training Data.” <i>Transactions on Machine Learning Research</i>. ML Research Press, 2022.","mla":"Iofinova, Eugenia B., et al. “FLEA: Provably Robust Fair Multisource Learning from Unreliable Training Data.” <i>Transactions on Machine Learning Research</i>, ML Research Press, 2022.","ieee":"E. B. Iofinova, N. H. Konstantinov, and C. Lampert, “FLEA: Provably robust fair multisource learning from unreliable training data,” <i>Transactions on Machine Learning Research</i>. ML Research Press, 2022.","short":"E.B. Iofinova, N.H. Konstantinov, C. Lampert, Transactions on Machine Learning Research (2022).","ista":"Iofinova EB, Konstantinov NH, Lampert C. 2022. FLEA: Provably robust fair multisource learning from unreliable training data. Transactions on Machine Learning Research.","ama":"Iofinova EB, Konstantinov NH, Lampert C. FLEA: Provably robust fair multisource learning from unreliable training data. <i>Transactions on Machine Learning Research</i>. 2022."},"tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)"},"day":"22","status":"public","external_id":{"arxiv":["2106.11732"]},"publication_status":"published","abstract":[{"lang":"eng","text":"Fairness-aware learning aims at constructing classifiers that not only make accurate predictions, but also do not discriminate against specific groups. It is a fast-growing area of\r\nmachine learning with far-reaching societal impact. However, existing fair learning methods\r\nare vulnerable to accidental or malicious artifacts in the training data, which can cause\r\nthem to unknowingly produce unfair classifiers. In this work we address the problem of\r\nfair learning from unreliable training data in the robust multisource setting, where the\r\navailable training data comes from multiple sources, a fraction of which might not be representative of the true data distribution. We introduce FLEA, a filtering-based algorithm\r\nthat identifies and suppresses those data sources that would have a negative impact on\r\nfairness or accuracy if they were used for training. As such, FLEA is not a replacement of\r\nprior fairness-aware learning methods but rather an augmentation that makes any of them\r\nrobust against unreliable training data. We show the effectiveness of our approach by a\r\ndiverse range of experiments on multiple datasets. Additionally, we prove formally that\r\n–given enough data– FLEA protects the learner against corruptions as long as the fraction of\r\naffected data sources is less than half. Our source code and documentation are available at\r\nhttps://github.com/ISTAustria-CVML/FLEA."}],"article_processing_charge":"No","title":"FLEA: Provably robust fair multisource learning from unreliable training data","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","author":[{"id":"f9a17499-f6e0-11ea-865d-fdf9a3f77117","orcid":"0000-0002-7778-3221","full_name":"Iofinova, Eugenia B","last_name":"Iofinova","first_name":"Eugenia B"},{"full_name":"Konstantinov, Nikola H","id":"4B9D76E4-F248-11E8-B48F-1D18A9856A87","orcid":"0009-0009-5204-7621","first_name":"Nikola H","last_name":"Konstantinov"},{"id":"40C20FD2-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-8622-7887","full_name":"Lampert, Christoph","first_name":"Christoph","last_name":"Lampert"}],"related_material":{"link":[{"description":"source code","relation":"software","url":"https://github.com/ISTAustria-CVML/FLEA"}]},"acknowledged_ssus":[{"_id":"ScienComp"}],"quality_controlled":"1","file":[{"file_name":"2022_TMLR_Iofinova.pdf","content_type":"application/pdf","date_created":"2023-02-23T10:30:04Z","success":1,"creator":"dernst","file_id":"12673","date_updated":"2023-02-23T10:30:04Z","file_size":1948063,"access_level":"open_access","relation":"main_file","checksum":"97c8a8470759cab597abb973ca137a3b"}],"corr_author":"1","ddc":["000"],"main_file_link":[{"url":"https://openreview.net/forum?id=XsPopigZXV","open_access":"1"}],"has_accepted_license":"1","date_created":"2023-02-02T20:29:57Z","year":"2022","publication":"Transactions on Machine Learning Research","publication_identifier":{"issn":["2835-8856"]}},{"type":"conference","acknowledgement":"Guy Avni: Work partially supported by the Israel Science Foundation, ISF grant agreement\r\nno 1679/21.\r\nThomas A. Henzinger: This work was supported in part by the ERC-2020-AdG 101020093.\r\nWe would like to thank all our collaborators Milad Aghajohari, Ventsislav Chonev, Rasmus Ibsen-Jensen, Ismäel Jecker, Petr Novotný, Josef Tkadlec, and Ðorđe Žikelić; we hope the collaboration was as fun and meaningful for you as it was for us.","oa_version":"Published Version","intvolume":"       241","_id":"12509","scopus_import":"1","oa":1,"file_date_updated":"2023-02-06T09:13:04Z","department":[{"_id":"ToHe"}],"publisher":"Schloss Dagstuhl - Leibniz-Zentrum für Informatik","date_updated":"2025-07-10T11:50:27Z","language":[{"iso":"eng"}],"month":"08","date_published":"2022-08-22T00:00:00Z","ec_funded":1,"tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)"},"day":"22","status":"public","series_title":"Leibniz International Proceedings in Informatics (LIPIcs)","place":"Dagstuhl, Germany","project":[{"_id":"62781420-2b32-11ec-9570-8d9b63373d4d","grant_number":"101020093","call_identifier":"H2020","name":"Vigilant Algorithmic Monitoring of Software"}],"citation":{"ista":"Avni G, Henzinger TA. 2022. An updated survey of bidding games on graphs. 47th International Symposium on Mathematical Foundations of Computer Science. MFCS: Mathematical Foundations of Computer ScienceLeibniz International Proceedings in Informatics (LIPIcs) vol. 241, 3:1-3:6.","ama":"Avni G, Henzinger TA. An updated survey of bidding games on graphs. In: <i>47th International Symposium on Mathematical Foundations of Computer Science</i>. Vol 241. Leibniz International Proceedings in Informatics (LIPIcs). Dagstuhl, Germany: Schloss Dagstuhl - Leibniz-Zentrum für Informatik; 2022:3:1-3:6. doi:<a href=\"https://doi.org/10.4230/LIPIcs.MFCS.2022.3\">10.4230/LIPIcs.MFCS.2022.3</a>","short":"G. Avni, T.A. Henzinger, in:, 47th International Symposium on Mathematical Foundations of Computer Science, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, Dagstuhl, Germany, 2022, p. 3:1-3:6.","ieee":"G. Avni and T. A. Henzinger, “An updated survey of bidding games on graphs,” in <i>47th International Symposium on Mathematical Foundations of Computer Science</i>, Vienna, Austria, 2022, vol. 241, p. 3:1-3:6.","mla":"Avni, Guy, and Thomas A. Henzinger. “An Updated Survey of Bidding Games on Graphs.” <i>47th International Symposium on Mathematical Foundations of Computer Science</i>, vol. 241, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2022, p. 3:1-3:6, doi:<a href=\"https://doi.org/10.4230/LIPIcs.MFCS.2022.3\">10.4230/LIPIcs.MFCS.2022.3</a>.","apa":"Avni, G., &#38; Henzinger, T. A. (2022). An updated survey of bidding games on graphs. In <i>47th International Symposium on Mathematical Foundations of Computer Science</i> (Vol. 241, p. 3:1-3:6). Dagstuhl, Germany: Schloss Dagstuhl - Leibniz-Zentrum für Informatik. <a href=\"https://doi.org/10.4230/LIPIcs.MFCS.2022.3\">https://doi.org/10.4230/LIPIcs.MFCS.2022.3</a>","chicago":"Avni, Guy, and Thomas A Henzinger. “An Updated Survey of Bidding Games on Graphs.” In <i>47th International Symposium on Mathematical Foundations of Computer Science</i>, 241:3:1-3:6. Leibniz International Proceedings in Informatics (LIPIcs). Dagstuhl, Germany: Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2022. <a href=\"https://doi.org/10.4230/LIPIcs.MFCS.2022.3\">https://doi.org/10.4230/LIPIcs.MFCS.2022.3</a>."},"volume":241,"author":[{"first_name":"Guy","last_name":"Avni","full_name":"Avni, Guy","id":"463C8BC2-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-5588-8287"},{"last_name":"Henzinger","first_name":"Thomas A","orcid":"0000-0002-2985-7724","id":"40876CD8-F248-11E8-B48F-1D18A9856A87","full_name":"Henzinger, Thomas A"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","abstract":[{"lang":"eng","text":"A graph game is a two-player zero-sum game in which the players move a token throughout a graph to produce an infinite path, which determines the winner or payoff of the game. In bidding games, both players have budgets, and in each turn, we hold an \"auction\" (bidding) to determine which player moves the token. In this survey, we consider several bidding mechanisms and their effect on the properties of the game. Specifically, bidding games, and in particular bidding games of infinite duration, have an intriguing equivalence with random-turn games in which in each turn, the player who moves is chosen randomly. We summarize how minor changes in the bidding mechanism lead to unexpected differences in the equivalence with random-turn games."}],"publication_status":"published","page":"3:1-3:6","article_processing_charge":"No","title":"An updated survey of bidding games on graphs","year":"2022","date_created":"2023-02-05T17:26:01Z","publication":"47th International Symposium on Mathematical Foundations of Computer Science","publication_identifier":{"issn":["1868-8969"],"isbn":["9783959772563"]},"doi":"10.4230/LIPIcs.MFCS.2022.3","file":[{"content_type":"application/pdf","file_name":"2022_LIPICs_Avni.pdf","date_created":"2023-02-06T09:13:04Z","creator":"dernst","success":1,"file_id":"12519","date_updated":"2023-02-06T09:13:04Z","file_size":624586,"checksum":"1888ec9421622f9526fbec2de035f132","relation":"main_file","access_level":"open_access"}],"quality_controlled":"1","corr_author":"1","conference":{"location":"Vienna, Austria","end_date":"2022-08-26","name":"MFCS: Mathematical Foundations of Computer Science","start_date":"2022-08-22"},"ddc":["000"],"has_accepted_license":"1"},{"publication":"Proceedings of the AAAI Conference on Artificial Intelligence","publication_identifier":{"isbn":["978577358350"],"issn":["2159-5399"],"eissn":["2374-3468"]},"doi":"10.1609/aaai.v36i6.20631","issue":"6","date_created":"2023-02-05T17:27:42Z","year":"2022","main_file_link":[{"url":"https://arxiv.org/abs/2107.08467","open_access":"1"}],"quality_controlled":"1","volume":36,"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","author":[{"full_name":"Gruenbacher, Sophie A.","last_name":"Gruenbacher","first_name":"Sophie A."},{"first_name":"Mathias","last_name":"Lechner","id":"3DC22916-F248-11E8-B48F-1D18A9856A87","full_name":"Lechner, Mathias"},{"full_name":"Hasani, Ramin","last_name":"Hasani","first_name":"Ramin"},{"full_name":"Rus, Daniela","last_name":"Rus","first_name":"Daniela"},{"full_name":"Henzinger, Thomas A","id":"40876CD8-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-2985-7724","first_name":"Thomas A","last_name":"Henzinger"},{"full_name":"Smolka, Scott A.","last_name":"Smolka","first_name":"Scott A."},{"last_name":"Grosu","first_name":"Radu","full_name":"Grosu, Radu"}],"keyword":["General Medicine"],"title":"GoTube: Scalable statistical verification of continuous-depth models","external_id":{"arxiv":["2107.08467"]},"publication_status":"published","abstract":[{"text":"We introduce a new statistical verification algorithm that formally quantifies the behavioral robustness of any time-continuous process formulated as a continuous-depth model. Our algorithm solves a set of global optimization (Go) problems over a given time horizon to construct a tight enclosure (Tube) of the set of all process executions starting from a ball of initial states. We call our algorithm GoTube. Through its construction, GoTube ensures that the bounding tube is conservative up to a desired probability and up to a desired tightness.\r\n GoTube is implemented in JAX and optimized to scale to complex continuous-depth neural network models. Compared to advanced reachability analysis tools for time-continuous neural networks, GoTube does not accumulate overapproximation errors between time steps and avoids the infamous wrapping effect inherent in symbolic techniques. We show that GoTube substantially outperforms state-of-the-art verification tools in terms of the size of the initial ball, speed, time-horizon, task completion, and scalability on a large set of experiments.\r\n GoTube is stable and sets the state-of-the-art in terms of its ability to scale to time horizons well beyond what has been previously possible.","lang":"eng"}],"article_processing_charge":"No","page":"6755-6764","status":"public","day":"28","ec_funded":1,"project":[{"name":"Formal methods for the design and analysis of complex systems","call_identifier":"FWF","grant_number":"Z211","_id":"25F42A32-B435-11E9-9278-68D0E5697425"},{"grant_number":"101020093","_id":"62781420-2b32-11ec-9570-8d9b63373d4d","name":"Vigilant Algorithmic Monitoring of Software","call_identifier":"H2020"}],"citation":{"short":"S.A. Gruenbacher, M. Lechner, R. Hasani, D. Rus, T.A. Henzinger, S.A. Smolka, R. Grosu, Proceedings of the AAAI Conference on Artificial Intelligence 36 (2022) 6755–6764.","ieee":"S. A. Gruenbacher <i>et al.</i>, “GoTube: Scalable statistical verification of continuous-depth models,” <i>Proceedings of the AAAI Conference on Artificial Intelligence</i>, vol. 36, no. 6. Association for the Advancement of Artificial Intelligence, pp. 6755–6764, 2022.","ama":"Gruenbacher SA, Lechner M, Hasani R, et al. GoTube: Scalable statistical verification of continuous-depth models. <i>Proceedings of the AAAI Conference on Artificial Intelligence</i>. 2022;36(6):6755-6764. doi:<a href=\"https://doi.org/10.1609/aaai.v36i6.20631\">10.1609/aaai.v36i6.20631</a>","ista":"Gruenbacher SA, Lechner M, Hasani R, Rus D, Henzinger TA, Smolka SA, Grosu R. 2022. GoTube: Scalable statistical verification of continuous-depth models. Proceedings of the AAAI Conference on Artificial Intelligence. 36(6), 6755–6764.","apa":"Gruenbacher, S. A., Lechner, M., Hasani, R., Rus, D., Henzinger, T. A., Smolka, S. A., &#38; Grosu, R. (2022). GoTube: Scalable statistical verification of continuous-depth models. <i>Proceedings of the AAAI Conference on Artificial Intelligence</i>. Association for the Advancement of Artificial Intelligence. <a href=\"https://doi.org/10.1609/aaai.v36i6.20631\">https://doi.org/10.1609/aaai.v36i6.20631</a>","chicago":"Gruenbacher, Sophie A., Mathias Lechner, Ramin Hasani, Daniela Rus, Thomas A Henzinger, Scott A. Smolka, and Radu Grosu. “GoTube: Scalable Statistical Verification of Continuous-Depth Models.” <i>Proceedings of the AAAI Conference on Artificial Intelligence</i>. Association for the Advancement of Artificial Intelligence, 2022. <a href=\"https://doi.org/10.1609/aaai.v36i6.20631\">https://doi.org/10.1609/aaai.v36i6.20631</a>.","mla":"Gruenbacher, Sophie A., et al. “GoTube: Scalable Statistical Verification of Continuous-Depth Models.” <i>Proceedings of the AAAI Conference on Artificial Intelligence</i>, vol. 36, no. 6, Association for the Advancement of Artificial Intelligence, 2022, pp. 6755–64, doi:<a href=\"https://doi.org/10.1609/aaai.v36i6.20631\">10.1609/aaai.v36i6.20631</a>."},"scopus_import":"1","_id":"12510","acknowledgement":"SG is funded by the Austrian Science Fund (FWF) project number W1255-N23. ML and TH are supported in part by FWF under grant Z211-N23 (Wittgenstein Award) and the ERC-2020-AdG 101020093. SS is supported by NSF awards DCL-2040599, CCF-1918225, and CPS-1446832. RH and DR are partially supported by Boeing. RG is partially supported by Horizon-2020 ECSEL Project grant No. 783163 (iDev40).","type":"journal_article","oa_version":"Preprint","intvolume":"        36","article_type":"original","date_updated":"2025-04-15T06:26:14Z","department":[{"_id":"ToHe"}],"publisher":"Association for the Advancement of Artificial Intelligence","arxiv":1,"date_published":"2022-06-28T00:00:00Z","month":"06","language":[{"iso":"eng"}],"oa":1},{"intvolume":"        36","oa_version":"Preprint","article_type":"original","type":"journal_article","acknowledgement":"This work was supported in part by the ERC-2020-AdG 101020093, ERC CoG 863818 (FoRM-SMArt) and the European Union’s Horizon 2020 research and innovation programme\r\nunder the Marie Skłodowska-Curie Grant Agreement No. 665385.","scopus_import":"1","_id":"12511","oa":1,"date_published":"2022-06-28T00:00:00Z","language":[{"iso":"eng"}],"month":"06","date_updated":"2026-04-07T13:27:55Z","department":[{"_id":"ToHe"},{"_id":"KrCh"}],"arxiv":1,"publisher":"Association for the Advancement of Artificial Intelligence","ec_funded":1,"status":"public","day":"28","citation":{"mla":"Lechner, Mathias, et al. “Stability Verification in Stochastic Control Systems via Neural Network Supermartingales.” <i>Proceedings of the AAAI Conference on Artificial Intelligence</i>, vol. 36, no. 7, Association for the Advancement of Artificial Intelligence, 2022, pp. 7326–36, doi:<a href=\"https://doi.org/10.1609/aaai.v36i7.20695\">10.1609/aaai.v36i7.20695</a>.","apa":"Lechner, M., Zikelic, D., Chatterjee, K., &#38; Henzinger, T. A. (2022). Stability verification in stochastic control systems via neural network supermartingales. <i>Proceedings of the AAAI Conference on Artificial Intelligence</i>. Association for the Advancement of Artificial Intelligence. <a href=\"https://doi.org/10.1609/aaai.v36i7.20695\">https://doi.org/10.1609/aaai.v36i7.20695</a>","chicago":"Lechner, Mathias, Dorde Zikelic, Krishnendu Chatterjee, and Thomas A Henzinger. “Stability Verification in Stochastic Control Systems via Neural Network Supermartingales.” <i>Proceedings of the AAAI Conference on Artificial Intelligence</i>. Association for the Advancement of Artificial Intelligence, 2022. <a href=\"https://doi.org/10.1609/aaai.v36i7.20695\">https://doi.org/10.1609/aaai.v36i7.20695</a>.","ista":"Lechner M, Zikelic D, Chatterjee K, Henzinger TA. 2022. Stability verification in stochastic control systems via neural network supermartingales. Proceedings of the AAAI Conference on Artificial Intelligence. 36(7), 7326–7336.","ama":"Lechner M, Zikelic D, Chatterjee K, Henzinger TA. Stability verification in stochastic control systems via neural network supermartingales. <i>Proceedings of the AAAI Conference on Artificial Intelligence</i>. 2022;36(7):7326-7336. doi:<a href=\"https://doi.org/10.1609/aaai.v36i7.20695\">10.1609/aaai.v36i7.20695</a>","ieee":"M. Lechner, D. Zikelic, K. Chatterjee, and T. A. Henzinger, “Stability verification in stochastic control systems via neural network supermartingales,” <i>Proceedings of the AAAI Conference on Artificial Intelligence</i>, vol. 36, no. 7. Association for the Advancement of Artificial Intelligence, pp. 7326–7336, 2022.","short":"M. Lechner, D. Zikelic, K. Chatterjee, T.A. Henzinger, Proceedings of the AAAI Conference on Artificial Intelligence 36 (2022) 7326–7336."},"project":[{"grant_number":"101020093","_id":"62781420-2b32-11ec-9570-8d9b63373d4d","name":"Vigilant Algorithmic Monitoring of Software","call_identifier":"H2020"},{"name":"Formal Methods for Stochastic Models: Algorithms and Applications","call_identifier":"H2020","grant_number":"863818","_id":"0599E47C-7A3F-11EA-A408-12923DDC885E"},{"call_identifier":"H2020","name":"International IST Doctoral Program","_id":"2564DBCA-B435-11E9-9278-68D0E5697425","grant_number":"665385"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","author":[{"id":"3DC22916-F248-11E8-B48F-1D18A9856A87","full_name":"Lechner, Mathias","last_name":"Lechner","first_name":"Mathias"},{"full_name":"Zikelic, Dorde","orcid":"0000-0002-4681-1699","id":"294AA7A6-F248-11E8-B48F-1D18A9856A87","first_name":"Dorde","last_name":"Zikelic"},{"first_name":"Krishnendu","last_name":"Chatterjee","orcid":"0000-0002-4561-241X","id":"2E5DCA20-F248-11E8-B48F-1D18A9856A87","full_name":"Chatterjee, Krishnendu"},{"full_name":"Henzinger, Thomas A","id":"40876CD8-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-2985-7724","first_name":"Thomas A","last_name":"Henzinger"}],"volume":36,"related_material":{"record":[{"id":"14539","relation":"dissertation_contains","status":"public"}]},"article_processing_charge":"No","page":"7326-7336","external_id":{"arxiv":["2112.09495"]},"publication_status":"published","abstract":[{"lang":"eng","text":"We consider the problem of formally verifying almost-sure (a.s.) asymptotic stability in discrete-time nonlinear stochastic control systems. While verifying stability in deterministic control systems is extensively studied in the literature, verifying stability in stochastic control systems is an open problem. The few existing works on this topic either consider only specialized forms of stochasticity or make restrictive assumptions on the system, rendering them inapplicable to learning algorithms with neural network policies. \r\n In this work, we present an approach for general nonlinear stochastic control problems with two novel aspects: (a) instead of classical stochastic extensions of Lyapunov functions, we use ranking supermartingales (RSMs) to certify a.s. asymptotic stability, and (b) we present a method for learning neural network RSMs. \r\n We prove that our approach guarantees a.s. asymptotic stability of the system and\r\n provides the first method to obtain bounds on the stabilization time, which stochastic Lyapunov functions do not.\r\n Finally, we validate our approach experimentally on a set of nonlinear stochastic reinforcement learning environments with neural network policies."}],"keyword":["General Medicine"],"title":"Stability verification in stochastic control systems via neural network supermartingales","date_created":"2023-02-05T17:29:50Z","year":"2022","doi":"10.1609/aaai.v36i7.20695","publication_identifier":{"eissn":["2374-3468"],"issn":["2159-5399"],"isbn":["9781577358350"]},"issue":"7","publication":"Proceedings of the AAAI Conference on Artificial Intelligence","corr_author":"1","quality_controlled":"1","main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/2112.09495"}]},{"isi":1,"oa":1,"language":[{"iso":"eng"}],"month":"12","date_published":"2022-12-21T00:00:00Z","publisher":"Springer Nature","department":[{"_id":"KrPi"}],"date_updated":"2024-10-09T21:04:05Z","oa_version":"Preprint","intvolume":"     13748","type":"conference","acknowledgement":"We are grateful to Devika Sharma and Luca Trevisan for their insight and advice and to an anonymous reviewer for helpful comments.\r\n\r\nThis work was supported by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (Grant agreement No. 101019547). The first author was additionally supported by RGC GRF CUHK14209920 and the fourth author was additionally supported by ISF grant No. 1399/17, project PROMETHEUS (Grant 780701), and Cariplo CRYPTONOMEX grant.","_id":"12516","scopus_import":"1","citation":{"apa":"Bogdanov, A., Cueto Noval, M., Hoffmann, C., &#38; Rosen, A. (2022). Public-Key Encryption from Homogeneous CLWE. In <i>Theory of Cryptography</i> (Vol. 13748, pp. 565–592). Chicago, IL, United States: Springer Nature. <a href=\"https://doi.org/10.1007/978-3-031-22365-5_20\">https://doi.org/10.1007/978-3-031-22365-5_20</a>","chicago":"Bogdanov, Andrej, Miguel Cueto Noval, Charlotte Hoffmann, and Alon Rosen. “Public-Key Encryption from Homogeneous CLWE.” In <i>Theory of Cryptography</i>, 13748:565–92. Springer Nature, 2022. <a href=\"https://doi.org/10.1007/978-3-031-22365-5_20\">https://doi.org/10.1007/978-3-031-22365-5_20</a>.","mla":"Bogdanov, Andrej, et al. “Public-Key Encryption from Homogeneous CLWE.” <i>Theory of Cryptography</i>, vol. 13748, Springer Nature, 2022, pp. 565–92, doi:<a href=\"https://doi.org/10.1007/978-3-031-22365-5_20\">10.1007/978-3-031-22365-5_20</a>.","short":"A. Bogdanov, M. Cueto Noval, C. Hoffmann, A. Rosen, in:, Theory of Cryptography, Springer Nature, 2022, pp. 565–592.","ieee":"A. Bogdanov, M. Cueto Noval, C. Hoffmann, and A. Rosen, “Public-Key Encryption from Homogeneous CLWE,” in <i>Theory of Cryptography</i>, Chicago, IL, United States, 2022, vol. 13748, pp. 565–592.","ama":"Bogdanov A, Cueto Noval M, Hoffmann C, Rosen A. Public-Key Encryption from Homogeneous CLWE. In: <i>Theory of Cryptography</i>. Vol 13748. Springer Nature; 2022:565-592. doi:<a href=\"https://doi.org/10.1007/978-3-031-22365-5_20\">10.1007/978-3-031-22365-5_20</a>","ista":"Bogdanov A, Cueto Noval M, Hoffmann C, Rosen A. 2022. Public-Key Encryption from Homogeneous CLWE. Theory of Cryptography. TCC: Theory of Cryptography, LNCS, vol. 13748, 565–592."},"alternative_title":["LNCS"],"day":"21","status":"public","page":"565-592","article_processing_charge":"No","abstract":[{"text":"The homogeneous continuous LWE (hCLWE) problem is to distinguish samples of a specific high-dimensional Gaussian mixture from standard normal samples. It was shown to be at least as hard as Learning with Errors, but no reduction in the other direction is currently known.\r\nWe present four new public-key encryption schemes based on the hardness of hCLWE, with varying tradeoffs between decryption and security errors, and different discretization techniques. Our schemes yield a polynomial-time algorithm for solving hCLWE using a Statistical Zero-Knowledge oracle.","lang":"eng"}],"external_id":{"isi":["000921318200020"]},"publication_status":"published","title":"Public-Key Encryption from Homogeneous CLWE","user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","author":[{"last_name":"Bogdanov","first_name":"Andrej","full_name":"Bogdanov, Andrej"},{"first_name":"Miguel","last_name":"Cueto Noval","orcid":"0000-0002-2505-4246","id":"ffc563a3-f6e0-11ea-865d-e3cce03d17cc","full_name":"Cueto Noval, Miguel"},{"full_name":"Hoffmann, Charlotte","id":"0f78d746-dc7d-11ea-9b2f-83f92091afe7","orcid":"0000-0003-2027-5549","first_name":"Charlotte","last_name":"Hoffmann"},{"first_name":"Alon","last_name":"Rosen","full_name":"Rosen, Alon"}],"volume":13748,"corr_author":"1","quality_controlled":"1","main_file_link":[{"open_access":"1","url":"https://eprint.iacr.org/2022/093"}],"conference":{"name":"TCC: Theory of Cryptography","start_date":"2022-11-07","end_date":"2022-11-10","location":"Chicago, IL, United States"},"year":"2022","date_created":"2023-02-05T23:01:00Z","publication_identifier":{"issn":["0302-9743"],"isbn":["9783031223648"],"eissn":["1611-3349"]},"doi":"10.1007/978-3-031-22365-5_20","publication":"Theory of Cryptography"},{"date_published":"2022-09-25T00:00:00Z","title":"Data for \"Majorana-like Coulomb spectroscopy in the absence of zero bias peaks\"","month":"09","date_updated":"2026-04-07T13:27:22Z","publisher":"Institute of Science and Technology Austria","department":[{"_id":"GeKa"}],"article_processing_charge":"No","file_date_updated":"2023-02-07T08:18:24Z","oa":1,"abstract":[{"text":"This .zip File contains the transport data, the codes for the data analysis, the microscopy analysis and the codes for the theoretical simulations for \"Majorana-like Coulomb spectroscopy in the absence of zero bias peaks\" by M. Valentini, et. al. The transport data are saved with hdf5 file format. The files can be open with the log browser of Labber.","lang":"eng"}],"related_material":{"record":[{"relation":"used_in_publication","id":"12118","status":"public"},{"relation":"used_in_publication","id":"13286","status":"public"}]},"_id":"12522","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","author":[{"last_name":"Valentini","first_name":"Marco","full_name":"Valentini, Marco","id":"C0BB2FAC-D767-11E9-B658-BC13E6697425"},{"full_name":"San-Jose, Pablo","first_name":"Pablo","last_name":"San-Jose"},{"full_name":"Arbiol, Jordi","last_name":"Arbiol","first_name":"Jordi"},{"last_name":"Marti-Sanchez","first_name":"Sara","full_name":"Marti-Sanchez, Sara"},{"last_name":"Botifoll","first_name":"Marc","full_name":"Botifoll, Marc"}],"oa_version":"Published Version","type":"research_data","has_accepted_license":"1","ddc":["530"],"citation":{"short":"M. Valentini, P. San-Jose, J. Arbiol, S. Marti-Sanchez, M. Botifoll, (2022).","ieee":"M. Valentini, P. San-Jose, J. Arbiol, S. Marti-Sanchez, and M. Botifoll, “Data for ‘Majorana-like Coulomb spectroscopy in the absence of zero bias peaks.’” Institute of Science and Technology Austria, 2022.","ista":"Valentini M, San-Jose P, Arbiol J, Marti-Sanchez S, Botifoll M. 2022. Data for ‘Majorana-like Coulomb spectroscopy in the absence of zero bias peaks’, Institute of Science and Technology Austria, <a href=\"https://doi.org/10.15479/AT:ISTA:12102\">10.15479/AT:ISTA:12102</a>.","ama":"Valentini M, San-Jose P, Arbiol J, Marti-Sanchez S, Botifoll M. Data for “Majorana-like Coulomb spectroscopy in the absence of zero bias peaks.” 2022. doi:<a href=\"https://doi.org/10.15479/AT:ISTA:12102\">10.15479/AT:ISTA:12102</a>","chicago":"Valentini, Marco, Pablo San-Jose, Jordi Arbiol, Sara Marti-Sanchez, and Marc Botifoll. “Data for ‘Majorana-like Coulomb Spectroscopy in the Absence of Zero Bias Peaks.’” Institute of Science and Technology Austria, 2022. <a href=\"https://doi.org/10.15479/AT:ISTA:12102\">https://doi.org/10.15479/AT:ISTA:12102</a>.","apa":"Valentini, M., San-Jose, P., Arbiol, J., Marti-Sanchez, S., &#38; Botifoll, M. (2022). Data for “Majorana-like Coulomb spectroscopy in the absence of zero bias peaks.” Institute of Science and Technology Austria. <a href=\"https://doi.org/10.15479/AT:ISTA:12102\">https://doi.org/10.15479/AT:ISTA:12102</a>","mla":"Valentini, Marco, et al. <i>Data for “Majorana-like Coulomb Spectroscopy in the Absence of Zero Bias Peaks.”</i> Institute of Science and Technology Austria, 2022, doi:<a href=\"https://doi.org/10.15479/AT:ISTA:12102\">10.15479/AT:ISTA:12102</a>."},"corr_author":"1","file":[{"date_updated":"2023-02-07T08:18:24Z","file_size":3609122411,"checksum":"0dbd6327bf84c7e81b295c4bc9d12826","relation":"main_file","access_level":"open_access","file_id":"12523","creator":"dernst","success":1,"content_type":"application/x-zip-compressed","file_name":"Majorana_like.zip","date_created":"2023-02-07T08:18:24Z"}],"doi":"10.15479/AT:ISTA:12102","day":"25","status":"public","date_created":"2023-02-07T08:13:39Z","year":"2022","tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)"},"contributor":[{"id":"C0BB2FAC-D767-11E9-B658-BC13E6697425","contributor_type":"contact_person","last_name":"Valentini","first_name":"Marco"}]},{"extern":"1","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","author":[{"full_name":"Banerjee, Tamajit","last_name":"Banerjee","first_name":"Tamajit"},{"last_name":"Majumdar","first_name":"Rupak","full_name":"Majumdar, Rupak"},{"full_name":"Mallik, Kaushik","id":"0834ff3c-6d72-11ec-94e0-b5b0a4fb8598","orcid":"0000-0001-9864-7475","last_name":"Mallik","first_name":"Kaushik"},{"full_name":"Schmuck, Anne-Kathrin","first_name":"Anne-Kathrin","last_name":"Schmuck"},{"first_name":"Sadegh","last_name":"Soudjani","full_name":"Soudjani, Sadegh"}],"volume":13244,"page":"81-98","article_processing_charge":"No","abstract":[{"text":"We consider turn-based stochastic 2-player games on graphs with ω-regular winning conditions. We provide a direct symbolic algorithm for solving such games when the winning condition is formulated as a Rabin condition. For a stochastic Rabin game with k pairs over a game graph with n vertices, our algorithm runs in O(nk+2k!) symbolic steps, which improves the state of the art.\r\nWe have implemented our symbolic algorithm, along with performance optimizations including parallellization and acceleration, in a BDD-based synthesis tool called Fairsyn. We demonstrate the superiority of Fairsyn compared to the state of the art on a set of synthetic benchmarks derived from the VLTS benchmark suite and on a control system benchmark from the literature. In our experiments, Fairsyn performed significantly faster with up to two orders of magnitude improvement in computation time.","lang":"eng"}],"publication_status":"published","title":"A direct symbolic algorithm for solving stochastic rabin games","year":"2022","date_created":"2023-02-08T11:43:34Z","publication_identifier":{"eisbn":["9783030995270"]},"doi":"10.1007/978-3-030-99527-0_5","publication":"28th International Conference on Tools and Algorithms for the Construction and Analysis of Systems","corr_author":"1","quality_controlled":"1","main_file_link":[{"url":"https://doi.org/10.1007/978-3-030-99527-0_5","open_access":"1"}],"conference":{"location":"Munich, Germany","end_date":"2022-04-07","name":"TACAS: Tools and Algorithms for the Construction and Analysis of Systems","start_date":"2022-04-02"},"intvolume":"     13244","oa_version":"Published Version","type":"conference","_id":"12529","scopus_import":"1","oa":1,"month":"03","language":[{"iso":"eng"}],"date_published":"2022-03-29T00:00:00Z","publisher":"Springer Nature","date_updated":"2024-10-09T21:04:10Z","alternative_title":["LNCS"],"day":"29","status":"public","citation":{"ista":"Banerjee T, Majumdar R, Mallik K, Schmuck A-K, Soudjani S. 2022. A direct symbolic algorithm for solving stochastic rabin games. 28th International Conference on Tools and Algorithms for the Construction and Analysis of Systems. TACAS: Tools and Algorithms for the Construction and Analysis of Systems, LNCS, vol. 13244, 81–98.","ama":"Banerjee T, Majumdar R, Mallik K, Schmuck A-K, Soudjani S. A direct symbolic algorithm for solving stochastic rabin games. In: <i>28th International Conference on Tools and Algorithms for the Construction and Analysis of Systems</i>. Vol 13244. Springer Nature; 2022:81-98. doi:<a href=\"https://doi.org/10.1007/978-3-030-99527-0_5\">10.1007/978-3-030-99527-0_5</a>","short":"T. Banerjee, R. Majumdar, K. Mallik, A.-K. Schmuck, S. Soudjani, in:, 28th International Conference on Tools and Algorithms for the Construction and Analysis of Systems, Springer Nature, 2022, pp. 81–98.","ieee":"T. Banerjee, R. Majumdar, K. Mallik, A.-K. Schmuck, and S. Soudjani, “A direct symbolic algorithm for solving stochastic rabin games,” in <i>28th International Conference on Tools and Algorithms for the Construction and Analysis of Systems</i>, Munich, Germany, 2022, vol. 13244, pp. 81–98.","mla":"Banerjee, Tamajit, et al. “A Direct Symbolic Algorithm for Solving Stochastic Rabin Games.” <i>28th International Conference on Tools and Algorithms for the Construction and Analysis of Systems</i>, vol. 13244, Springer Nature, 2022, pp. 81–98, doi:<a href=\"https://doi.org/10.1007/978-3-030-99527-0_5\">10.1007/978-3-030-99527-0_5</a>.","apa":"Banerjee, T., Majumdar, R., Mallik, K., Schmuck, A.-K., &#38; Soudjani, S. (2022). A direct symbolic algorithm for solving stochastic rabin games. In <i>28th International Conference on Tools and Algorithms for the Construction and Analysis of Systems</i> (Vol. 13244, pp. 81–98). Munich, Germany: Springer Nature. <a href=\"https://doi.org/10.1007/978-3-030-99527-0_5\">https://doi.org/10.1007/978-3-030-99527-0_5</a>","chicago":"Banerjee, Tamajit, Rupak Majumdar, Kaushik Mallik, Anne-Kathrin Schmuck, and Sadegh Soudjani. “A Direct Symbolic Algorithm for Solving Stochastic Rabin Games.” In <i>28th International Conference on Tools and Algorithms for the Construction and Analysis of Systems</i>, 13244:81–98. Springer Nature, 2022. <a href=\"https://doi.org/10.1007/978-3-030-99527-0_5\">https://doi.org/10.1007/978-3-030-99527-0_5</a>."}},{"_id":"12530","scopus_import":"1","extern":"1","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","author":[{"last_name":"Finkbeiner","first_name":"Bernd","full_name":"Finkbeiner, Bernd"},{"id":"0834ff3c-6d72-11ec-94e0-b5b0a4fb8598","orcid":"0000-0001-9864-7475","full_name":"Mallik, Kaushik","last_name":"Mallik","first_name":"Kaushik"},{"last_name":"Passing","first_name":"Noemi","full_name":"Passing, Noemi"},{"first_name":"Malte","last_name":"Schledjewski","full_name":"Schledjewski, Malte"},{"last_name":"Schmuck","first_name":"Anne-Kathrin","full_name":"Schmuck, Anne-Kathrin"}],"oa_version":"None","type":"conference","title":"BOCoSy: Small but powerful symbolic output-feedback control","month":"05","language":[{"iso":"eng"}],"date_published":"2022-05-01T00:00:00Z","publisher":"ACM","date_updated":"2023-02-09T08:53:13Z","page":"24:1-24:11","article_processing_charge":"No","abstract":[{"text":"We present BOCoSy, a tool for Bounded symbolic Output-feedback Controller Synthesis. Given a specification, BOCoSy synthesizes symbolic output-feedback controllers which interact with a given plant via a pre-defined finite symbolic interface. BOCoSy solves this problem by a new lazy abstraction-refinement technique which starts with a very coarse abstraction of the external trace semantics of the given plant and iteratively removes non-admissible behavior from this abstract model until a controller is found. BOCoSy steers the search for controllers towards small and concise state space representations by utilizing ideas from bounded synthesis. As a result, BOCoSy returns small and explainable controllers that are still powerful enough to solve the given synthesis problem. We show that BOCoSy is able to synthesize small, human readable symbolic controllers quickly on a set of benchmarks.","lang":"eng"}],"publication_status":"published","publication_identifier":{"isbn":["9781450391962"]},"doi":"10.1145/3501710.3519535","day":"01","status":"public","publication":"25th ACM International Conference on Hybrid Systems: Computation and Control","year":"2022","date_created":"2023-02-08T11:43:50Z","conference":{"end_date":"2022-05-06","location":"Milan, Italy","name":"HSCC: International Conference on Hybrid Systems Computation and Control","start_date":"2022-05-04"},"citation":{"short":"B. Finkbeiner, K. Mallik, N. Passing, M. Schledjewski, A.-K. Schmuck, in:, 25th ACM International Conference on Hybrid Systems: Computation and Control, ACM, 2022, p. 24:1-24:11.","ieee":"B. Finkbeiner, K. Mallik, N. Passing, M. Schledjewski, and A.-K. Schmuck, “BOCoSy: Small but powerful symbolic output-feedback control,” in <i>25th ACM International Conference on Hybrid Systems: Computation and Control</i>, Milan, Italy, 2022, p. 24:1-24:11.","ama":"Finkbeiner B, Mallik K, Passing N, Schledjewski M, Schmuck A-K. BOCoSy: Small but powerful symbolic output-feedback control. In: <i>25th ACM International Conference on Hybrid Systems: Computation and Control</i>. ACM; 2022:24:1-24:11. doi:<a href=\"https://doi.org/10.1145/3501710.3519535\">10.1145/3501710.3519535</a>","ista":"Finkbeiner B, Mallik K, Passing N, Schledjewski M, Schmuck A-K. 2022. BOCoSy: Small but powerful symbolic output-feedback control. 25th ACM International Conference on Hybrid Systems: Computation and Control. HSCC: International Conference on Hybrid Systems Computation and Control, 24:1-24:11.","chicago":"Finkbeiner, Bernd, Kaushik Mallik, Noemi Passing, Malte Schledjewski, and Anne-Kathrin Schmuck. “BOCoSy: Small but Powerful Symbolic Output-Feedback Control.” In <i>25th ACM International Conference on Hybrid Systems: Computation and Control</i>, 24:1-24:11. ACM, 2022. <a href=\"https://doi.org/10.1145/3501710.3519535\">https://doi.org/10.1145/3501710.3519535</a>.","apa":"Finkbeiner, B., Mallik, K., Passing, N., Schledjewski, M., &#38; Schmuck, A.-K. (2022). BOCoSy: Small but powerful symbolic output-feedback control. In <i>25th ACM International Conference on Hybrid Systems: Computation and Control</i> (p. 24:1-24:11). Milan, Italy: ACM. <a href=\"https://doi.org/10.1145/3501710.3519535\">https://doi.org/10.1145/3501710.3519535</a>","mla":"Finkbeiner, Bernd, et al. “BOCoSy: Small but Powerful Symbolic Output-Feedback Control.” <i>25th ACM International Conference on Hybrid Systems: Computation and Control</i>, ACM, 2022, p. 24:1-24:11, doi:<a href=\"https://doi.org/10.1145/3501710.3519535\">10.1145/3501710.3519535</a>."},"quality_controlled":"1"},{"year":"2022","date_created":"2023-02-10T13:46:37Z","publication":"36th Conference on Neural Information Processing Systems","publication_identifier":{"eissn":["1049-5258"],"isbn":["9781713871088"]},"quality_controlled":"1","corr_author":"1","conference":{"name":"NeurIPS: Neural Information Processing Systems","start_date":"2022-11-28","end_date":"2022-12-09","location":"New Orleans, LA, United States"},"main_file_link":[{"url":" https://doi.org/10.48550/arXiv.2205.10217","open_access":"1"}],"volume":35,"OA_place":"repository","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","author":[{"last_name":"Bombari","first_name":"Simone","full_name":"Bombari, Simone","id":"ca726dda-de17-11ea-bc14-f9da834f63aa"},{"full_name":"Amani, Mohammad Hossein","last_name":"Amani","first_name":"Mohammad Hossein"},{"id":"27EB676C-8706-11E9-9510-7717E6697425","orcid":"0000-0002-3242-7020","full_name":"Mondelli, Marco","first_name":"Marco","last_name":"Mondelli"}],"abstract":[{"lang":"eng","text":"The Neural Tangent Kernel (NTK) has emerged as a powerful tool to provide memorization, optimization and generalization guarantees in deep neural networks. A line of work has studied the NTK spectrum for two-layer and deep networks with at least a layer with Ω(N) neurons, N being the number of training samples. Furthermore, there is increasing evidence suggesting that deep networks with sub-linear layer widths are powerful memorizers and optimizers, as long as the number of parameters exceeds the number of samples. Thus, a natural open question is whether the NTK is well conditioned in such a challenging sub-linear setup. In this paper, we answer this question in the affirmative. Our key technical contribution is a lower bound on the smallest NTK eigenvalue for deep networks with the minimum possible over-parameterization: the number of parameters is roughly Ω(N) and, hence, the number of neurons is as little as Ω(N−−√). To showcase the applicability of our NTK bounds, we provide two results concerning memorization capacity and optimization guarantees for gradient descent training."}],"external_id":{"arxiv":["2205.10217"]},"publication_status":"published","page":"7628-7640","article_processing_charge":"No","title":"Memorization and optimization in deep neural networks with minimum over-parameterization","OA_type":"green","day":"24","status":"public","alternative_title":["Advances in Neural Information Processing Systems"],"project":[{"_id":"059876FA-7A3F-11EA-A408-12923DDC885E","name":"Prix Lopez-Loretta 2019 - Marco Mondelli"}],"citation":{"ista":"Bombari S, Amani MH, Mondelli M. 2022. Memorization and optimization in deep neural networks with minimum over-parameterization. 36th Conference on Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems, Advances in Neural Information Processing Systems, vol. 35, 7628–7640.","ama":"Bombari S, Amani MH, Mondelli M. Memorization and optimization in deep neural networks with minimum over-parameterization. In: <i>36th Conference on Neural Information Processing Systems</i>. Vol 35. Neural Information Processing Systems Foundation; 2022:7628-7640.","short":"S. Bombari, M.H. Amani, M. Mondelli, in:, 36th Conference on Neural Information Processing Systems, Neural Information Processing Systems Foundation, 2022, pp. 7628–7640.","ieee":"S. Bombari, M. H. Amani, and M. Mondelli, “Memorization and optimization in deep neural networks with minimum over-parameterization,” in <i>36th Conference on Neural Information Processing Systems</i>, New Orleans, LA, United States, 2022, vol. 35, pp. 7628–7640.","mla":"Bombari, Simone, et al. “Memorization and Optimization in Deep Neural Networks with Minimum Over-Parameterization.” <i>36th Conference on Neural Information Processing Systems</i>, vol. 35, Neural Information Processing Systems Foundation, 2022, pp. 7628–40.","apa":"Bombari, S., Amani, M. H., &#38; Mondelli, M. (2022). Memorization and optimization in deep neural networks with minimum over-parameterization. In <i>36th Conference on Neural Information Processing Systems</i> (Vol. 35, pp. 7628–7640). New Orleans, LA, United States: Neural Information Processing Systems Foundation.","chicago":"Bombari, Simone, Mohammad Hossein Amani, and Marco Mondelli. “Memorization and Optimization in Deep Neural Networks with Minimum Over-Parameterization.” In <i>36th Conference on Neural Information Processing Systems</i>, 35:7628–40. Neural Information Processing Systems Foundation, 2022."},"acknowledgement":"The authors were partially supported by the 2019 Lopez-Loreta prize, and they would like to thank\r\nQuynh Nguyen, Mahdi Soltanolkotabi and Adel Javanmard for helpful discussions.\r\n","type":"conference","oa_version":"Preprint","intvolume":"        35","_id":"12537","oa":1,"department":[{"_id":"MaMo"}],"arxiv":1,"publisher":"Neural Information Processing Systems Foundation","date_updated":"2025-05-14T11:28:22Z","language":[{"iso":"eng"}],"month":"07","date_published":"2022-07-24T00:00:00Z"},{"citation":{"short":"M.H. Amani, S. Bombari, M. Mondelli, R. Pukdee, S. Rini, IEEE Information Theory Workshop (2022) 588–593.","ieee":"M. H. Amani, S. Bombari, M. Mondelli, R. Pukdee, and S. Rini, “Sharp asymptotics on the compression of two-layer neural networks,” <i>IEEE Information Theory Workshop</i>. IEEE, pp. 588–593, 2022.","ama":"Amani MH, Bombari S, Mondelli M, Pukdee R, Rini S. Sharp asymptotics on the compression of two-layer neural networks. <i>IEEE Information Theory Workshop</i>. 2022:588-593. doi:<a href=\"https://doi.org/10.1109/ITW54588.2022.9965870\">10.1109/ITW54588.2022.9965870</a>","ista":"Amani MH, Bombari S, Mondelli M, Pukdee R, Rini S. 2022. Sharp asymptotics on the compression of two-layer neural networks. IEEE Information Theory Workshop., 588–593.","chicago":"Amani, Mohammad Hossein, Simone Bombari, Marco Mondelli, Rattana Pukdee, and Stefano Rini. “Sharp Asymptotics on the Compression of Two-Layer Neural Networks.” <i>IEEE Information Theory Workshop</i>. IEEE, 2022. <a href=\"https://doi.org/10.1109/ITW54588.2022.9965870\">https://doi.org/10.1109/ITW54588.2022.9965870</a>.","apa":"Amani, M. H., Bombari, S., Mondelli, M., Pukdee, R., &#38; Rini, S. (2022). Sharp asymptotics on the compression of two-layer neural networks. <i>IEEE Information Theory Workshop</i>. Mumbai, India: IEEE. <a href=\"https://doi.org/10.1109/ITW54588.2022.9965870\">https://doi.org/10.1109/ITW54588.2022.9965870</a>","mla":"Amani, Mohammad Hossein, et al. “Sharp Asymptotics on the Compression of Two-Layer Neural Networks.” <i>IEEE Information Theory Workshop</i>, IEEE, 2022, pp. 588–93, doi:<a href=\"https://doi.org/10.1109/ITW54588.2022.9965870\">10.1109/ITW54588.2022.9965870</a>."},"day":"16","status":"public","isi":1,"oa":1,"language":[{"iso":"eng"}],"month":"11","date_published":"2022-11-16T00:00:00Z","arxiv":1,"publisher":"IEEE","department":[{"_id":"MaMo"}],"date_updated":"2025-09-10T09:53:31Z","article_type":"original","oa_version":"Preprint","type":"journal_article","_id":"12538","scopus_import":"1","quality_controlled":"1","main_file_link":[{"open_access":"1","url":" https://doi.org/10.48550/arXiv.2205.08199"}],"conference":{"location":"Mumbai, India","end_date":"2022-11-09","start_date":"2022-11-01","name":"ITW: Information Theory Workshop"},"year":"2022","date_created":"2023-02-10T13:47:56Z","publication_identifier":{"isbn":["9781665483414"]},"doi":"10.1109/ITW54588.2022.9965870","publication":"IEEE Information Theory Workshop","page":"588-593","article_processing_charge":"No","abstract":[{"text":"In this paper, we study the compression of a target two-layer neural network with N nodes into a compressed network with M<N nodes. More precisely, we consider the setting in which the weights of the target network are i.i.d. sub-Gaussian, and we minimize the population L_2 loss between the outputs of the target and of the compressed network, under the assumption of Gaussian inputs. By using tools from high-dimensional probability, we show that this non-convex problem can be simplified when the target network is sufficiently over-parameterized, and provide the error rate of this approximation as a function of the input dimension and N. In this mean-field limit, the simplified objective, as well as the optimal weights of the compressed network, does not depend on the realization of the target network, but only on expected scaling factors. Furthermore, for networks with ReLU activation, we conjecture that the optimum of the simplified optimization problem is achieved by taking weights on the Equiangular Tight Frame (ETF), while the scaling of the weights and the orientation of the ETF depend on the parameters of the target network. Numerical evidence is provided to support this conjecture.","lang":"eng"}],"external_id":{"isi":["000904341100099"],"arxiv":["2205.08199"]},"publication_status":"published","title":"Sharp asymptotics on the compression of two-layer neural networks","user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","author":[{"full_name":"Amani, Mohammad Hossein","last_name":"Amani","first_name":"Mohammad Hossein"},{"first_name":"Simone","last_name":"Bombari","id":"ca726dda-de17-11ea-bc14-f9da834f63aa","full_name":"Bombari, Simone"},{"full_name":"Mondelli, Marco","id":"27EB676C-8706-11E9-9510-7717E6697425","orcid":"0000-0002-3242-7020","first_name":"Marco","last_name":"Mondelli"},{"first_name":"Rattana","last_name":"Pukdee","full_name":"Pukdee, Rattana"},{"full_name":"Rini, Stefano","last_name":"Rini","first_name":"Stefano"}]},{"citation":{"ieee":"R. Venkataramanan, K. Kögler, and M. Mondelli, “Estimation in rotationally invariant generalized linear models via approximate message passing,” in <i>Proceedings of the 39th International Conference on Machine Learning</i>, Baltimore, MD, United States, 2022, vol. 162.","short":"R. Venkataramanan, K. Kögler, M. Mondelli, in:, Proceedings of the 39th International Conference on Machine Learning, ML Research Press, 2022.","ista":"Venkataramanan R, Kögler K, Mondelli M. 2022. Estimation in rotationally invariant generalized linear models via approximate message passing. Proceedings of the 39th International Conference on Machine Learning. ICML: International Conference on Machine Learning vol. 162, 22.","ama":"Venkataramanan R, Kögler K, Mondelli M. Estimation in rotationally invariant generalized linear models via approximate message passing. In: <i>Proceedings of the 39th International Conference on Machine Learning</i>. Vol 162. ML Research Press; 2022.","chicago":"Venkataramanan, Ramji, Kevin Kögler, and Marco Mondelli. “Estimation in Rotationally Invariant Generalized Linear Models via Approximate Message Passing.” In <i>Proceedings of the 39th International Conference on Machine Learning</i>, Vol. 162. ML Research Press, 2022.","apa":"Venkataramanan, R., Kögler, K., &#38; Mondelli, M. (2022). Estimation in rotationally invariant generalized linear models via approximate message passing. In <i>Proceedings of the 39th International Conference on Machine Learning</i> (Vol. 162). Baltimore, MD, United States: ML Research Press.","mla":"Venkataramanan, Ramji, et al. “Estimation in Rotationally Invariant Generalized Linear Models via Approximate Message Passing.” <i>Proceedings of the 39th International Conference on Machine Learning</i>, vol. 162, 22, ML Research Press, 2022."},"project":[{"_id":"059876FA-7A3F-11EA-A408-12923DDC885E","name":"Prix Lopez-Loretta 2019 - Marco Mondelli"}],"status":"public","oa":1,"file_date_updated":"2023-02-13T10:53:11Z","language":[{"iso":"eng"}],"date_published":"2022-01-01T00:00:00Z","department":[{"_id":"MaMo"}],"publisher":"ML Research Press","date_updated":"2025-04-15T07:50:16Z","intvolume":"       162","oa_version":"Published Version","type":"conference","acknowledgement":"The authors would like to thank the anonymous reviewers for their helpful comments. KK and MM were partially supported by the 2019 Lopez-Loreta Prize.","_id":"12540","corr_author":"1","quality_controlled":"1","file":[{"success":1,"creator":"dernst","file_name":"2022_PMLR_Venkataramanan.pdf","content_type":"application/pdf","date_created":"2023-02-13T10:53:11Z","date_updated":"2023-02-13T10:53:11Z","file_size":2341343,"access_level":"open_access","relation":"main_file","checksum":"67436eb0a660789514cdf9db79e84683","file_id":"12547"}],"has_accepted_license":"1","conference":{"name":"ICML: International Conference on Machine Learning","start_date":"2022-07-17","location":"Baltimore, MD, United States","end_date":"2022-07-23"},"ddc":["000"],"year":"2022","date_created":"2023-02-10T13:49:04Z","article_number":"22","publication":"Proceedings of the 39th International Conference on Machine Learning","article_processing_charge":"No","abstract":[{"text":"We consider the problem of signal estimation in generalized linear models defined via rotationally invariant design matrices. Since these matrices can have an arbitrary spectral distribution, this model is well suited for capturing complex correlation structures which often arise in applications. We propose a novel family of approximate message passing (AMP) algorithms for signal estimation, and rigorously characterize their performance in the high-dimensional limit via a state evolution recursion. Our rotationally invariant AMP has complexity of the same order as the existing AMP derived under the restrictive assumption of a Gaussian design; our algorithm also recovers this existing AMP as a special case. Numerical results showcase a performance close to Vector AMP (which is conjectured to be Bayes-optimal in some settings), but obtained with a much lower complexity, as the proposed algorithm does not require a computationally expensive singular value decomposition.","lang":"eng"}],"publication_status":"published","title":"Estimation in rotationally invariant generalized linear models via approximate message passing","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","author":[{"last_name":"Venkataramanan","first_name":"Ramji","full_name":"Venkataramanan, Ramji"},{"first_name":"Kevin","last_name":"Kögler","id":"94ec913c-dc85-11ea-9058-e5051ab2428b","full_name":"Kögler, Kevin"},{"id":"27EB676C-8706-11E9-9510-7717E6697425","orcid":"0000-0002-3242-7020","full_name":"Mondelli, Marco","last_name":"Mondelli","first_name":"Marco"}],"volume":162},{"scopus_import":"1","_id":"12568","intvolume":"        36","oa_version":"Preprint","type":"conference","date_published":"2022-06-28T00:00:00Z","month":"06","language":[{"iso":"eng"}],"date_updated":"2024-10-09T21:04:32Z","department":[{"_id":"KrCh"}],"arxiv":1,"publisher":"Association for the Advancement of Artificial Intelligence","oa":1,"status":"public","day":"28","citation":{"short":"T. Meggendorfer, in:, Proceedings of the 36th AAAI Conference on Artificial Intelligence, AAAI 2022, Association for the Advancement of Artificial Intelligence, 2022, pp. 9858–9867.","ieee":"T. Meggendorfer, “Risk-aware stochastic shortest path,” in <i>Proceedings of the 36th AAAI Conference on Artificial Intelligence, AAAI 2022</i>, Virtual, 2022, vol. 36, no. 9, pp. 9858–9867.","ista":"Meggendorfer T. 2022. Risk-aware stochastic shortest path. Proceedings of the 36th AAAI Conference on Artificial Intelligence, AAAI 2022. Conference on Artificial Intelligence vol. 36, 9858–9867.","ama":"Meggendorfer T. Risk-aware stochastic shortest path. In: <i>Proceedings of the 36th AAAI Conference on Artificial Intelligence, AAAI 2022</i>. Vol 36. Association for the Advancement of Artificial Intelligence; 2022:9858-9867. doi:<a href=\"https://doi.org/10.1609/aaai.v36i9.21222\">10.1609/aaai.v36i9.21222</a>","chicago":"Meggendorfer, Tobias. “Risk-Aware Stochastic Shortest Path.” In <i>Proceedings of the 36th AAAI Conference on Artificial Intelligence, AAAI 2022</i>, 36:9858–67. Association for the Advancement of Artificial Intelligence, 2022. <a href=\"https://doi.org/10.1609/aaai.v36i9.21222\">https://doi.org/10.1609/aaai.v36i9.21222</a>.","apa":"Meggendorfer, T. (2022). Risk-aware stochastic shortest path. In <i>Proceedings of the 36th AAAI Conference on Artificial Intelligence, AAAI 2022</i> (Vol. 36, pp. 9858–9867). Virtual: Association for the Advancement of Artificial Intelligence. <a href=\"https://doi.org/10.1609/aaai.v36i9.21222\">https://doi.org/10.1609/aaai.v36i9.21222</a>","mla":"Meggendorfer, Tobias. “Risk-Aware Stochastic Shortest Path.” <i>Proceedings of the 36th AAAI Conference on Artificial Intelligence, AAAI 2022</i>, vol. 36, no. 9, Association for the Advancement of Artificial Intelligence, 2022, pp. 9858–67, doi:<a href=\"https://doi.org/10.1609/aaai.v36i9.21222\">10.1609/aaai.v36i9.21222</a>."},"author":[{"last_name":"Meggendorfer","first_name":"Tobias","full_name":"Meggendorfer, Tobias","id":"b21b0c15-30a2-11eb-80dc-f13ca25802e1","orcid":"0000-0002-1712-2165"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","volume":36,"title":"Risk-aware stochastic shortest path","article_processing_charge":"No","page":"9858-9867","external_id":{"arxiv":["2203.01640"]},"publication_status":"published","abstract":[{"lang":"eng","text":"We treat the problem of risk-aware control for stochastic shortest path (SSP) on Markov decision processes (MDP). Typically, expectation is considered for SSP, which however is oblivious to the incurred risk. We present an alternative view, instead optimizing conditional value-at-risk (CVaR), an established risk measure. We treat both Markov chains as well as MDP and introduce, through novel insights, two algorithms, based on linear programming and value iteration, respectively. Both algorithms offer precise and provably correct solutions. Evaluation of our prototype implementation shows that risk-aware control is feasible on several moderately sized models."}],"doi":"10.1609/aaai.v36i9.21222","publication_identifier":{"isbn":["1577358767"],"eissn":["2374-3468"]},"issue":"9","publication":"Proceedings of the 36th AAAI Conference on Artificial Intelligence, AAAI 2022","date_created":"2023-02-19T23:00:56Z","year":"2022","main_file_link":[{"url":" https://doi.org/10.48550/arXiv.2203.01640","open_access":"1"}],"conference":{"location":"Virtual","end_date":"2022-03-01","name":"Conference on Artificial Intelligence","start_date":"2022-02-22"},"corr_author":"1","quality_controlled":"1"},{"title":"Sub-seasonal variability of supraglacial ice cliff melt rates and associated processes from time-lapse photogrammetry","keyword":["Earth-Surface Processes","Water Science and Technology"],"abstract":[{"text":"Melt from supraglacial ice cliffs is an important contributor to the mass loss of debris-covered glaciers. However, ice cliff contribution is difficult to quantify as they are highly dynamic features, and the paucity of observations of melt rates and their variability leads to large modelling uncertainties. We quantify monsoon season melt and 3D evolution of four ice cliffs over two debris-covered glaciers in High Mountain Asia (Langtang Glacier, Nepal, and 24K Glacier, China) at very high resolution using terrestrial photogrammetry applied to imagery captured from time-lapse cameras installed on lateral moraines. We derive weekly flow-corrected digital elevation models (DEMs) of the glacier surface with a maximum vertical bias of ±0.2 m for Langtang Glacier and ±0.05 m for 24K Glacier and use change detection to determine distributed melt rates at the surfaces of the ice cliffs throughout the study period. We compare the measured melt patterns with those derived from a 3D energy balance model to derive the contribution of the main energy fluxes. We find that ice cliff melt varies considerably throughout the melt season, with maximum melt rates of 5 to 8 cm d−1, and their average melt rates are 11–14 (Langtang) and 4.5 (24K) times higher than the surrounding debris-covered ice. Our results highlight the influence of redistributed supraglacial debris on cliff melt. At both sites, ice cliff albedo is influenced by the presence of thin debris at the ice cliff surface, which is largely controlled on 24K Glacier by liquid precipitation events that wash away this debris. Slightly thicker or patchy debris reduces melt by 1–3 cm d−1 at all sites. Ultimately, our observations show a strong spatio-temporal variability in cliff area at each site, which is controlled by supraglacial streams and ponds and englacial cavities that promote debris slope destabilisation and the lateral expansion of the cliffs. These findings highlight the need to better represent processes of debris redistribution in ice cliff models, to in turn improve estimates of ice cliff contribution to glacier melt and the long-term geomorphological evolution of debris-covered glacier surfaces.","lang":"eng"}],"publication_status":"published","page":"4701-4725","article_processing_charge":"No","volume":16,"extern":"1","author":[{"full_name":"Kneib, Marin","first_name":"Marin","last_name":"Kneib"},{"first_name":"Evan S.","last_name":"Miles","full_name":"Miles, Evan S."},{"first_name":"Pascal","last_name":"Buri","full_name":"Buri, Pascal"},{"full_name":"Fugger, Stefan","last_name":"Fugger","first_name":"Stefan"},{"full_name":"McCarthy, Michael","last_name":"McCarthy","first_name":"Michael"},{"full_name":"Shaw, Thomas E.","first_name":"Thomas E.","last_name":"Shaw"},{"first_name":"Zhao","last_name":"Chuanxi","full_name":"Chuanxi, Zhao"},{"full_name":"Truffer, Martin","last_name":"Truffer","first_name":"Martin"},{"first_name":"Matthew J.","last_name":"Westoby","full_name":"Westoby, Matthew J."},{"full_name":"Yang, Wei","last_name":"Yang","first_name":"Wei"},{"id":"b28f055a-81ea-11ed-b70c-a9fe7f7b0e70","full_name":"Pellicciotti, Francesca","last_name":"Pellicciotti","first_name":"Francesca"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","main_file_link":[{"open_access":"1","url":"https://doi.org/10.5194/tc-16-4701-2022"}],"quality_controlled":"1","publication":"The Cryosphere","issue":"11","publication_identifier":{"issn":["1994-0424"]},"doi":"10.5194/tc-16-4701-2022","year":"2022","date_created":"2023-02-20T08:09:42Z","publisher":"Copernicus Publications","date_updated":"2023-02-28T13:59:22Z","month":"11","language":[{"iso":"eng"}],"date_published":"2022-11-11T00:00:00Z","oa":1,"_id":"12574","scopus_import":"1","type":"journal_article","article_type":"original","intvolume":"        16","oa_version":"Published Version","citation":{"apa":"Kneib, M., Miles, E. S., Buri, P., Fugger, S., McCarthy, M., Shaw, T. E., … Pellicciotti, F. (2022). Sub-seasonal variability of supraglacial ice cliff melt rates and associated processes from time-lapse photogrammetry. <i>The Cryosphere</i>. Copernicus Publications. <a href=\"https://doi.org/10.5194/tc-16-4701-2022\">https://doi.org/10.5194/tc-16-4701-2022</a>","chicago":"Kneib, Marin, Evan S. Miles, Pascal Buri, Stefan Fugger, Michael McCarthy, Thomas E. Shaw, Zhao Chuanxi, et al. “Sub-Seasonal Variability of Supraglacial Ice Cliff Melt Rates and Associated Processes from Time-Lapse Photogrammetry.” <i>The Cryosphere</i>. Copernicus Publications, 2022. <a href=\"https://doi.org/10.5194/tc-16-4701-2022\">https://doi.org/10.5194/tc-16-4701-2022</a>.","mla":"Kneib, Marin, et al. “Sub-Seasonal Variability of Supraglacial Ice Cliff Melt Rates and Associated Processes from Time-Lapse Photogrammetry.” <i>The Cryosphere</i>, vol. 16, no. 11, Copernicus Publications, 2022, pp. 4701–25, doi:<a href=\"https://doi.org/10.5194/tc-16-4701-2022\">10.5194/tc-16-4701-2022</a>.","short":"M. Kneib, E.S. Miles, P. Buri, S. Fugger, M. McCarthy, T.E. Shaw, Z. Chuanxi, M. Truffer, M.J. Westoby, W. Yang, F. Pellicciotti, The Cryosphere 16 (2022) 4701–4725.","ieee":"M. Kneib <i>et al.</i>, “Sub-seasonal variability of supraglacial ice cliff melt rates and associated processes from time-lapse photogrammetry,” <i>The Cryosphere</i>, vol. 16, no. 11. Copernicus Publications, pp. 4701–4725, 2022.","ama":"Kneib M, Miles ES, Buri P, et al. Sub-seasonal variability of supraglacial ice cliff melt rates and associated processes from time-lapse photogrammetry. <i>The Cryosphere</i>. 2022;16(11):4701-4725. doi:<a href=\"https://doi.org/10.5194/tc-16-4701-2022\">10.5194/tc-16-4701-2022</a>","ista":"Kneib M, Miles ES, Buri P, Fugger S, McCarthy M, Shaw TE, Chuanxi Z, Truffer M, Westoby MJ, Yang W, Pellicciotti F. 2022. Sub-seasonal variability of supraglacial ice cliff melt rates and associated processes from time-lapse photogrammetry. The Cryosphere. 16(11), 4701–4725."},"status":"public","day":"11"},{"volume":10,"author":[{"last_name":"McCarthy","first_name":"Michael","full_name":"McCarthy, Michael"},{"full_name":"Meier, Fabienne","last_name":"Meier","first_name":"Fabienne"},{"first_name":"Simone","last_name":"Fatichi","full_name":"Fatichi, Simone"},{"full_name":"Stocker, Benjamin D.","first_name":"Benjamin D.","last_name":"Stocker"},{"full_name":"Shaw, Thomas E.","last_name":"Shaw","first_name":"Thomas E."},{"last_name":"Miles","first_name":"Evan","full_name":"Miles, Evan"},{"full_name":"Dussaillant, Inés","last_name":"Dussaillant","first_name":"Inés"},{"id":"b28f055a-81ea-11ed-b70c-a9fe7f7b0e70","full_name":"Pellicciotti, Francesca","first_name":"Francesca","last_name":"Pellicciotti"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","extern":"1","publication_status":"published","abstract":[{"text":"The current Chilean megadrought has led to acute water shortages in central Chile since 2010. Glaciers have provided vital fresh water to the region's rivers, but the quantity, timing and sustainability of that provision remain unclear. Here we combine in-situ, remote sensing and climate reanalysis data to show that from 2010 to 2018 during the megadrought, unsustainable imbalance ablation of glaciers (ablation not balanced by new snowfall) strongly buffered the late-summer discharge of the Maipo River, a primary source of water to Santiago. If there had been no glaciers, water availability would have been reduced from December through May, with a 31 ± 19% decrease during March. Our results indicate that while the annual contributions of imbalance ablation to river discharge during the megadrought have been small compared to those from precipitation and sustainable balance ablation, they have nevertheless been a substantial input to a hydrological system that was already experiencing high water stress. The water-equivalent volume of imbalance ablation generated in the Maipo Basin between 2010 and 2018 was 740 × 106 m3 (19 ± 12 mm yr−1), approximately 3.4 times the capacity of the basin's El Yeso Reservoir. This is equivalent to 14% of Santiago's potable water use in that time, while total glacier ablation was equivalent to 59%. We show that glacier retreat will exacerbate river discharge deficits and further jeopardize water availability in central Chile if precipitation deficits endure, and conjecture that these effects will be amplified by climatic warming.","lang":"eng"}],"article_processing_charge":"No","keyword":["Earth and Planetary Sciences (miscellaneous)","General Environmental Science"],"title":"Glacier contributions to river discharge during the current Chilean megadrought","article_number":"e2022EF002852","date_created":"2023-02-20T08:09:49Z","year":"2022","publication":"Earth's Future","publication_identifier":{"issn":["2328-4277"]},"doi":"10.1029/2022ef002852","issue":"10","quality_controlled":"1","main_file_link":[{"open_access":"1","url":"https://doi.org/10.1029/2022EF002852"}],"type":"journal_article","oa_version":"Published Version","intvolume":"        10","article_type":"original","scopus_import":"1","_id":"12575","oa":1,"date_updated":"2023-02-28T13:55:32Z","publisher":"American Geophysical Union","date_published":"2022-10-01T00:00:00Z","language":[{"iso":"eng"}],"month":"10","day":"01","status":"public","citation":{"mla":"McCarthy, Michael, et al. “Glacier Contributions to River Discharge during the Current Chilean Megadrought.” <i>Earth’s Future</i>, vol. 10, no. 10, e2022EF002852, American Geophysical Union, 2022, doi:<a href=\"https://doi.org/10.1029/2022ef002852\">10.1029/2022ef002852</a>.","chicago":"McCarthy, Michael, Fabienne Meier, Simone Fatichi, Benjamin D. Stocker, Thomas E. Shaw, Evan Miles, Inés Dussaillant, and Francesca Pellicciotti. “Glacier Contributions to River Discharge during the Current Chilean Megadrought.” <i>Earth’s Future</i>. American Geophysical Union, 2022. <a href=\"https://doi.org/10.1029/2022ef002852\">https://doi.org/10.1029/2022ef002852</a>.","apa":"McCarthy, M., Meier, F., Fatichi, S., Stocker, B. D., Shaw, T. E., Miles, E., … Pellicciotti, F. (2022). Glacier contributions to river discharge during the current Chilean megadrought. <i>Earth’s Future</i>. American Geophysical Union. <a href=\"https://doi.org/10.1029/2022ef002852\">https://doi.org/10.1029/2022ef002852</a>","ama":"McCarthy M, Meier F, Fatichi S, et al. Glacier contributions to river discharge during the current Chilean megadrought. <i>Earth’s Future</i>. 2022;10(10). doi:<a href=\"https://doi.org/10.1029/2022ef002852\">10.1029/2022ef002852</a>","ista":"McCarthy M, Meier F, Fatichi S, Stocker BD, Shaw TE, Miles E, Dussaillant I, Pellicciotti F. 2022. Glacier contributions to river discharge during the current Chilean megadrought. Earth’s Future. 10(10), e2022EF002852.","ieee":"M. McCarthy <i>et al.</i>, “Glacier contributions to river discharge during the current Chilean megadrought,” <i>Earth’s Future</i>, vol. 10, no. 10. American Geophysical Union, 2022.","short":"M. McCarthy, F. Meier, S. Fatichi, B.D. Stocker, T.E. Shaw, E. Miles, I. Dussaillant, F. Pellicciotti, Earth’s Future 10 (2022)."}},{"publication_status":"published","abstract":[{"text":"Glacier health across High Mountain Asia (HMA) is highly heterogeneous and strongly governed by regional climate, which is variably influenced by monsoon dynamics and the westerlies. We explore four decades of glacier energy and mass balance at three climatically distinct sites across HMA by utilising a detailed land surface model driven by bias-corrected Weather Research and Forecasting meteorological forcing. All three glaciers have experienced long-term mass losses (ranging from −0.04 ± 0.09 to −0.59 ± 0.20 m w.e. a<jats:sup>−1</jats:sup>) consistent with widespread warming across the region. However, complex and contrasting responses of glacier energy and mass balance to the patterns of the Indian Summer Monsoon were evident, largely driven by the role snowfall timing, amount and phase. A later monsoon onset generates less total snowfall to the glacier in the southeastern Tibetan Plateau during May–June, augmenting net shortwave radiation and affecting annual mass balance (−0.5 m w.e. on average compared to early onset years). Conversely, timing of the monsoon’s arrival has limited impact for the Nepalese Himalaya which is more strongly governed by the temperature and snowfall amount during the core monsoon season. In the arid central Tibetan Plateau, a later monsoon arrival results in a 40 mm (58%) increase of May–June snowfall on average compared to early onset years, likely driven by the greater interaction of westerly storm events. Meanwhile, a late monsoon cessation at this site sees an average 200 mm (192%) increase in late summer precipitation due to monsoonal storms. A trend towards weaker intensity monsoon conditions in recent decades, combined with long-term warming patterns, has produced predominantly negative glacier mass balances for all sites (up to 1 m w.e. more mass loss in the Nepalese Himalaya compared to strong monsoon intensity years) but sub-regional variability in monsoon timing can additionally complicate this response.","lang":"eng"}],"article_processing_charge":"No","keyword":["Public Health","Environmental and Occupational Health","General Environmental Science","Renewable Energy","Sustainability and the Environment"],"title":"Multi-decadal monsoon characteristics and glacier response in High Mountain Asia","volume":17,"author":[{"last_name":"Shaw","first_name":"T E","full_name":"Shaw, T E"},{"full_name":"Miles, E S","last_name":"Miles","first_name":"E S"},{"first_name":"D","last_name":"Chen","full_name":"Chen, D"},{"full_name":"Jouberton, A","last_name":"Jouberton","first_name":"A"},{"last_name":"Kneib","first_name":"M","full_name":"Kneib, M"},{"first_name":"S","last_name":"Fugger","full_name":"Fugger, S"},{"last_name":"Ou","first_name":"T","full_name":"Ou, T"},{"full_name":"Lai, H-W","first_name":"H-W","last_name":"Lai"},{"full_name":"Fujita, K","last_name":"Fujita","first_name":"K"},{"full_name":"Yang, W","last_name":"Yang","first_name":"W"},{"first_name":"S","last_name":"Fatichi","full_name":"Fatichi, S"},{"first_name":"Francesca","last_name":"Pellicciotti","id":"b28f055a-81ea-11ed-b70c-a9fe7f7b0e70","full_name":"Pellicciotti, Francesca"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","extern":"1","quality_controlled":"1","main_file_link":[{"open_access":"1","url":"https://doi.org/10.1088/1748-9326/ac9008"}],"article_number":"104001","date_created":"2023-02-20T08:09:56Z","year":"2022","publication":"Environmental Research Letters","publication_identifier":{"issn":["1748-9326"]},"doi":"10.1088/1748-9326/ac9008","issue":"10","oa":1,"date_updated":"2023-02-28T13:53:16Z","publisher":"IOP Publishing","date_published":"2022-09-16T00:00:00Z","language":[{"iso":"eng"}],"month":"09","type":"journal_article","intvolume":"        17","oa_version":"Published Version","article_type":"letter_note","scopus_import":"1","_id":"12576","citation":{"ieee":"T. E. Shaw <i>et al.</i>, “Multi-decadal monsoon characteristics and glacier response in High Mountain Asia,” <i>Environmental Research Letters</i>, vol. 17, no. 10. IOP Publishing, 2022.","short":"T.E. Shaw, E.S. Miles, D. Chen, A. Jouberton, M. Kneib, S. Fugger, T. Ou, H.-W. Lai, K. Fujita, W. Yang, S. Fatichi, F. Pellicciotti, Environmental Research Letters 17 (2022).","ista":"Shaw TE, Miles ES, Chen D, Jouberton A, Kneib M, Fugger S, Ou T, Lai H-W, Fujita K, Yang W, Fatichi S, Pellicciotti F. 2022. Multi-decadal monsoon characteristics and glacier response in High Mountain Asia. Environmental Research Letters. 17(10), 104001.","ama":"Shaw TE, Miles ES, Chen D, et al. Multi-decadal monsoon characteristics and glacier response in High Mountain Asia. <i>Environmental Research Letters</i>. 2022;17(10). doi:<a href=\"https://doi.org/10.1088/1748-9326/ac9008\">10.1088/1748-9326/ac9008</a>","chicago":"Shaw, T E, E S Miles, D Chen, A Jouberton, M Kneib, S Fugger, T Ou, et al. “Multi-Decadal Monsoon Characteristics and Glacier Response in High Mountain Asia.” <i>Environmental Research Letters</i>. IOP Publishing, 2022. <a href=\"https://doi.org/10.1088/1748-9326/ac9008\">https://doi.org/10.1088/1748-9326/ac9008</a>.","apa":"Shaw, T. E., Miles, E. S., Chen, D., Jouberton, A., Kneib, M., Fugger, S., … Pellicciotti, F. (2022). Multi-decadal monsoon characteristics and glacier response in High Mountain Asia. <i>Environmental Research Letters</i>. IOP Publishing. <a href=\"https://doi.org/10.1088/1748-9326/ac9008\">https://doi.org/10.1088/1748-9326/ac9008</a>","mla":"Shaw, T. E., et al. “Multi-Decadal Monsoon Characteristics and Glacier Response in High Mountain Asia.” <i>Environmental Research Letters</i>, vol. 17, no. 10, 104001, IOP Publishing, 2022, doi:<a href=\"https://doi.org/10.1088/1748-9326/ac9008\">10.1088/1748-9326/ac9008</a>."},"status":"public","day":"16"},{"issue":"37","doi":"10.1073/pnas.2109796119","publication_identifier":{"eissn":["1091-6490"],"issn":["0027-8424"]},"publication":"PNAS","year":"2022","date_created":"2023-02-20T08:10:02Z","article_number":"e2109796119","quality_controlled":"1","extern":"1","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","author":[{"first_name":"Achille","last_name":"Jouberton","full_name":"Jouberton, Achille"},{"first_name":"Thomas E.","last_name":"Shaw","full_name":"Shaw, Thomas E."},{"first_name":"Evan","last_name":"Miles","full_name":"Miles, Evan"},{"first_name":"Michael","last_name":"McCarthy","full_name":"McCarthy, Michael"},{"first_name":"Stefan","last_name":"Fugger","full_name":"Fugger, Stefan"},{"first_name":"Shaoting","last_name":"Ren","full_name":"Ren, Shaoting"},{"full_name":"Dehecq, Amaury","last_name":"Dehecq","first_name":"Amaury"},{"full_name":"Yang, Wei","last_name":"Yang","first_name":"Wei"},{"first_name":"Francesca","last_name":"Pellicciotti","full_name":"Pellicciotti, Francesca","id":"b28f055a-81ea-11ed-b70c-a9fe7f7b0e70"}],"volume":119,"title":"Warming-induced monsoon precipitation phase change intensifies glacier mass loss in the southeastern Tibetan Plateau","keyword":["Multidisciplinary"],"article_processing_charge":"No","abstract":[{"text":"Glaciers are key components of the mountain water towers of Asia and are vital for downstream domestic, agricultural, and industrial uses. The glacier mass loss rate over the southeastern Tibetan Plateau is among the highest in Asia and has accelerated in recent decades. This acceleration has been attributed to increased warming, but the mechanisms behind these glaciers’ high sensitivity to warming remain unclear, while the influence of changes in precipitation over the past decades is poorly quantified. Here, we reconstruct glacier mass changes and catchment runoff since 1975 at a benchmark glacier, Parlung No. 4, to shed light on the drivers of recent mass losses for the monsoonal, spring-accumulation glaciers of the Tibetan Plateau. Our modeling demonstrates how a temperature increase (mean of 0.39<jats:sup>∘</jats:sup>C ⋅dec<jats:sup>−1</jats:sup>since 1990) has accelerated mass loss rates by altering both the ablation and accumulation regimes in a complex manner. The majority of the post-2000 mass loss occurred during the monsoon months, caused by simultaneous decreases in the solid precipitation ratio (from 0.70 to 0.56) and precipitation amount (–10%), leading to reduced monsoon accumulation (–26%). Higher solid precipitation in spring (+18%) during the last two decades was increasingly important in mitigating glacier mass loss by providing mass to the glacier and protecting it from melting in the early monsoon. With bare ice exposed to warmer temperatures for longer periods, icemelt and catchment discharge have unsustainably intensified since the start of the 21st century, raising concerns for long-term water supply and hazard occurrence in the region.","lang":"eng"}],"publication_status":"published","day":"06","status":"public","citation":{"ieee":"A. Jouberton <i>et al.</i>, “Warming-induced monsoon precipitation phase change intensifies glacier mass loss in the southeastern Tibetan Plateau,” <i>PNAS</i>, vol. 119, no. 37. Proceedings of the National Academy of Sciences, 2022.","short":"A. Jouberton, T.E. Shaw, E. Miles, M. McCarthy, S. Fugger, S. Ren, A. Dehecq, W. Yang, F. Pellicciotti, PNAS 119 (2022).","ista":"Jouberton A, Shaw TE, Miles E, McCarthy M, Fugger S, Ren S, Dehecq A, Yang W, Pellicciotti F. 2022. Warming-induced monsoon precipitation phase change intensifies glacier mass loss in the southeastern Tibetan Plateau. PNAS. 119(37), e2109796119.","ama":"Jouberton A, Shaw TE, Miles E, et al. Warming-induced monsoon precipitation phase change intensifies glacier mass loss in the southeastern Tibetan Plateau. <i>PNAS</i>. 2022;119(37). doi:<a href=\"https://doi.org/10.1073/pnas.2109796119\">10.1073/pnas.2109796119</a>","apa":"Jouberton, A., Shaw, T. E., Miles, E., McCarthy, M., Fugger, S., Ren, S., … Pellicciotti, F. (2022). Warming-induced monsoon precipitation phase change intensifies glacier mass loss in the southeastern Tibetan Plateau. <i>PNAS</i>. Proceedings of the National Academy of Sciences. <a href=\"https://doi.org/10.1073/pnas.2109796119\">https://doi.org/10.1073/pnas.2109796119</a>","chicago":"Jouberton, Achille, Thomas E. Shaw, Evan Miles, Michael McCarthy, Stefan Fugger, Shaoting Ren, Amaury Dehecq, Wei Yang, and Francesca Pellicciotti. “Warming-Induced Monsoon Precipitation Phase Change Intensifies Glacier Mass Loss in the Southeastern Tibetan Plateau.” <i>PNAS</i>. Proceedings of the National Academy of Sciences, 2022. <a href=\"https://doi.org/10.1073/pnas.2109796119\">https://doi.org/10.1073/pnas.2109796119</a>.","mla":"Jouberton, Achille, et al. “Warming-Induced Monsoon Precipitation Phase Change Intensifies Glacier Mass Loss in the Southeastern Tibetan Plateau.” <i>PNAS</i>, vol. 119, no. 37, e2109796119, Proceedings of the National Academy of Sciences, 2022, doi:<a href=\"https://doi.org/10.1073/pnas.2109796119\">10.1073/pnas.2109796119</a>."},"_id":"12577","scopus_import":"1","article_type":"original","oa_version":"None","intvolume":"       119","type":"journal_article","month":"09","language":[{"iso":"eng"}],"date_published":"2022-09-06T00:00:00Z","publisher":"Proceedings of the National Academy of Sciences","date_updated":"2023-02-28T13:50:37Z"},{"main_file_link":[{"url":"https://doi.org/10.5194/tc-16-1697-2022","open_access":"1"}],"quality_controlled":"1","issue":"5","doi":"10.5194/tc-16-1697-2022","publication_identifier":{"issn":["1994-0424"]},"publication":"The Cryosphere","year":"2022","date_created":"2023-02-20T08:10:09Z","title":"Modelling supraglacial debris-cover evolution from the single-glacier to the regional scale: An application to High Mountain Asia","keyword":["Earth-Surface Processes","Water Science and Technology"],"page":"1697-1718","article_processing_charge":"No","abstract":[{"lang":"eng","text":"Currently, about 12 %–13 % of High Mountain Asia’s glacier area is debris-covered, which alters its surface mass balance. However, in regional-scale modelling approaches, debris-covered glaciers are typically treated as clean-ice glaciers, leading to a bias when modelling their future evolution. Here, we present a new approach for modelling debris area and thickness evolution, applicable from single glaciers to the global scale. We derive a parameterization and implement it as a module into the Global Glacier Evolution Model (GloGEMflow), a combined mass-balance ice-flow model. The module is initialized with both glacier-specific observations of the debris' spatial distribution and estimates of debris thickness. These data sets account for the fact that debris can either enhance or reduce surface melt depending on thickness. Our model approach also enables representing the spatiotemporal evolution of debris extent and thickness. We calibrate and evaluate the module on a selected subset of glaciers and apply GloGEMflow using different climate scenarios to project the future evolution of all glaciers in High Mountain Asia until 2100. Explicitly accounting for debris cover has only a minor effect on the projected mass loss, which is in line with previous projections. Despite this small effect, we argue that the improved process representation is of added value when aiming at capturing intra-glacier scales, i.e. spatial mass-balance distribution.\r\nDepending on the climate scenario, the mean debris-cover fraction is expected to increase, while mean debris thickness is projected to show only minor changes, although large local thickening is expected. To isolate the influence of explicitly accounting for supraglacial debris cover, we re-compute glacier evolution without the debris-cover module. We show that glacier geometry, area, volume, and flow velocity evolve differently, especially at the level of individual glaciers. This highlights the importance of accounting for debris cover and its spatiotemporal evolution when projecting future glacier changes."}],"publication_status":"published","extern":"1","author":[{"first_name":"Loris","last_name":"Compagno","full_name":"Compagno, Loris"},{"full_name":"Huss, Matthias","first_name":"Matthias","last_name":"Huss"},{"full_name":"Miles, Evan Stewart","last_name":"Miles","first_name":"Evan Stewart"},{"last_name":"McCarthy","first_name":"Michael James","full_name":"McCarthy, Michael James"},{"last_name":"Zekollari","first_name":"Harry","full_name":"Zekollari, Harry"},{"full_name":"Dehecq, Amaury","first_name":"Amaury","last_name":"Dehecq"},{"first_name":"Francesca","last_name":"Pellicciotti","id":"b28f055a-81ea-11ed-b70c-a9fe7f7b0e70","full_name":"Pellicciotti, Francesca"},{"first_name":"Daniel","last_name":"Farinotti","full_name":"Farinotti, Daniel"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","volume":16,"citation":{"short":"L. Compagno, M. Huss, E.S. Miles, M.J. McCarthy, H. Zekollari, A. Dehecq, F. Pellicciotti, D. Farinotti, The Cryosphere 16 (2022) 1697–1718.","ieee":"L. Compagno <i>et al.</i>, “Modelling supraglacial debris-cover evolution from the single-glacier to the regional scale: An application to High Mountain Asia,” <i>The Cryosphere</i>, vol. 16, no. 5. Copernicus Publications, pp. 1697–1718, 2022.","ama":"Compagno L, Huss M, Miles ES, et al. Modelling supraglacial debris-cover evolution from the single-glacier to the regional scale: An application to High Mountain Asia. <i>The Cryosphere</i>. 2022;16(5):1697-1718. doi:<a href=\"https://doi.org/10.5194/tc-16-1697-2022\">10.5194/tc-16-1697-2022</a>","ista":"Compagno L, Huss M, Miles ES, McCarthy MJ, Zekollari H, Dehecq A, Pellicciotti F, Farinotti D. 2022. Modelling supraglacial debris-cover evolution from the single-glacier to the regional scale: An application to High Mountain Asia. The Cryosphere. 16(5), 1697–1718.","chicago":"Compagno, Loris, Matthias Huss, Evan Stewart Miles, Michael James McCarthy, Harry Zekollari, Amaury Dehecq, Francesca Pellicciotti, and Daniel Farinotti. “Modelling Supraglacial Debris-Cover Evolution from the Single-Glacier to the Regional Scale: An Application to High Mountain Asia.” <i>The Cryosphere</i>. Copernicus Publications, 2022. <a href=\"https://doi.org/10.5194/tc-16-1697-2022\">https://doi.org/10.5194/tc-16-1697-2022</a>.","apa":"Compagno, L., Huss, M., Miles, E. S., McCarthy, M. J., Zekollari, H., Dehecq, A., … Farinotti, D. (2022). Modelling supraglacial debris-cover evolution from the single-glacier to the regional scale: An application to High Mountain Asia. <i>The Cryosphere</i>. Copernicus Publications. <a href=\"https://doi.org/10.5194/tc-16-1697-2022\">https://doi.org/10.5194/tc-16-1697-2022</a>","mla":"Compagno, Loris, et al. “Modelling Supraglacial Debris-Cover Evolution from the Single-Glacier to the Regional Scale: An Application to High Mountain Asia.” <i>The Cryosphere</i>, vol. 16, no. 5, Copernicus Publications, 2022, pp. 1697–718, doi:<a href=\"https://doi.org/10.5194/tc-16-1697-2022\">10.5194/tc-16-1697-2022</a>."},"day":"05","status":"public","month":"05","language":[{"iso":"eng"}],"date_published":"2022-05-05T00:00:00Z","publisher":"Copernicus Publications","date_updated":"2023-02-28T13:47:17Z","oa":1,"_id":"12578","scopus_import":"1","article_type":"original","oa_version":"Published Version","intvolume":"        16","type":"journal_article"},{"author":[{"last_name":"Fugger","first_name":"Stefan","full_name":"Fugger, Stefan"},{"first_name":"Catriona L.","last_name":"Fyffe","full_name":"Fyffe, Catriona L."},{"first_name":"Simone","last_name":"Fatichi","full_name":"Fatichi, Simone"},{"last_name":"Miles","first_name":"Evan","full_name":"Miles, Evan"},{"last_name":"McCarthy","first_name":"Michael","full_name":"McCarthy, Michael"},{"first_name":"Thomas E.","last_name":"Shaw","full_name":"Shaw, Thomas E."},{"full_name":"Ding, Baohong","first_name":"Baohong","last_name":"Ding"},{"first_name":"Wei","last_name":"Yang","full_name":"Yang, Wei"},{"first_name":"Patrick","last_name":"Wagnon","full_name":"Wagnon, Patrick"},{"last_name":"Immerzeel","first_name":"Walter","full_name":"Immerzeel, Walter"},{"full_name":"Liu, Qiao","last_name":"Liu","first_name":"Qiao"},{"last_name":"Pellicciotti","first_name":"Francesca","id":"b28f055a-81ea-11ed-b70c-a9fe7f7b0e70","full_name":"Pellicciotti, Francesca"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","extern":"1","volume":16,"keyword":["Earth-Surface Processes","Water Science and Technology"],"title":"Understanding monsoon controls on the energy and mass balance of glaciers in the Central and Eastern Himalaya","article_processing_charge":"No","page":"1631-1652","publication_status":"published","abstract":[{"text":"The Indian and East Asian summer monsoons shape the melt and accumulation patterns of glaciers in High Mountain Asia in complex ways due to the interaction of persistent cloud cover, large temperature ranges, high atmospheric water content and high precipitation rates. Glacier energy- and mass-balance modelling using in situ measurements offers insights into the ways in which surface processes are shaped by climatic regimes. In this study, we use a full energy- and mass-balance model and seven on-glacier automatic weather station datasets from different parts of the Central and Eastern Himalaya to investigate how monsoon conditions influence the glacier surface energy and mass balance. In particular, we look at how debris-covered and debris-free glaciers respond differently to monsoonal conditions.\r\nThe radiation budget primarily controls the melt of clean-ice glaciers, but turbulent fluxes play an important role in modulating the melt energy on debris-covered glaciers. The sensible heat flux decreases during core monsoon, but the latent heat flux cools the surface due to evaporation of liquid water. This interplay of radiative and turbulent fluxes causes debris-covered glacier melt rates to stay almost constant through the different phases of the monsoon. Ice melt under thin debris, on the other hand, is amplified by both the dark surface and the turbulent fluxes, which intensify melt during monsoon through surface heating and condensation.\r\nPre-monsoon snow cover can considerably delay melt onset and have a strong impact on the seasonal mass balance. Intermittent monsoon snow cover lowers the melt rates at high elevation. This work is fundamental to the understanding of the present and future Himalayan cryosphere and water budget, while informing and motivating further glacier- and catchment-scale research using process-based models.","lang":"eng"}],"doi":"10.5194/tc-16-1631-2022","publication_identifier":{"issn":["1994-0424"]},"issue":"5","publication":"The Cryosphere","date_created":"2023-02-20T08:10:16Z","year":"2022","main_file_link":[{"url":"https://doi.org/10.5194/tc-16-1631-2022","open_access":"1"}],"quality_controlled":"1","scopus_import":"1","_id":"12579","intvolume":"        16","oa_version":"Published Version","article_type":"original","type":"journal_article","date_published":"2022-05-05T00:00:00Z","month":"05","language":[{"iso":"eng"}],"date_updated":"2023-02-28T13:45:01Z","publisher":"Copernicus Publications","oa":1,"status":"public","day":"05","citation":{"apa":"Fugger, S., Fyffe, C. L., Fatichi, S., Miles, E., McCarthy, M., Shaw, T. E., … Pellicciotti, F. (2022). Understanding monsoon controls on the energy and mass balance of glaciers in the Central and Eastern Himalaya. <i>The Cryosphere</i>. Copernicus Publications. <a href=\"https://doi.org/10.5194/tc-16-1631-2022\">https://doi.org/10.5194/tc-16-1631-2022</a>","chicago":"Fugger, Stefan, Catriona L. Fyffe, Simone Fatichi, Evan Miles, Michael McCarthy, Thomas E. Shaw, Baohong Ding, et al. “Understanding Monsoon Controls on the Energy and Mass Balance of Glaciers in the Central and Eastern Himalaya.” <i>The Cryosphere</i>. Copernicus Publications, 2022. <a href=\"https://doi.org/10.5194/tc-16-1631-2022\">https://doi.org/10.5194/tc-16-1631-2022</a>.","mla":"Fugger, Stefan, et al. “Understanding Monsoon Controls on the Energy and Mass Balance of Glaciers in the Central and Eastern Himalaya.” <i>The Cryosphere</i>, vol. 16, no. 5, Copernicus Publications, 2022, pp. 1631–52, doi:<a href=\"https://doi.org/10.5194/tc-16-1631-2022\">10.5194/tc-16-1631-2022</a>.","ieee":"S. Fugger <i>et al.</i>, “Understanding monsoon controls on the energy and mass balance of glaciers in the Central and Eastern Himalaya,” <i>The Cryosphere</i>, vol. 16, no. 5. Copernicus Publications, pp. 1631–1652, 2022.","short":"S. Fugger, C.L. Fyffe, S. Fatichi, E. Miles, M. McCarthy, T.E. Shaw, B. Ding, W. Yang, P. Wagnon, W. Immerzeel, Q. Liu, F. Pellicciotti, The Cryosphere 16 (2022) 1631–1652.","ama":"Fugger S, Fyffe CL, Fatichi S, et al. Understanding monsoon controls on the energy and mass balance of glaciers in the Central and Eastern Himalaya. <i>The Cryosphere</i>. 2022;16(5):1631-1652. doi:<a href=\"https://doi.org/10.5194/tc-16-1631-2022\">10.5194/tc-16-1631-2022</a>","ista":"Fugger S, Fyffe CL, Fatichi S, Miles E, McCarthy M, Shaw TE, Ding B, Yang W, Wagnon P, Immerzeel W, Liu Q, Pellicciotti F. 2022. Understanding monsoon controls on the energy and mass balance of glaciers in the Central and Eastern Himalaya. The Cryosphere. 16(5), 1631–1652."}}]