[{"day":"01","article_processing_charge":"No","type":"journal_article","user_id":"ba8df636-2132-11f1-aed0-ed93e2281fdd","publication":"Urban Climate","date_created":"2026-07-27T12:30:24Z","_id":"22564","date_published":"2022-12-01T00:00:00Z","year":"2022","status":"public","doi":"10.1016/j.uclim.2022.101346","keyword":["Urban heat island","Urban dry island","Boundary layer","Convective clouds","Analytical model"],"date_updated":"2026-08-06T14:03:31Z","tmp":{"image":"/images/cc_by.png","short":"CC BY (4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)"},"article_type":"original","oa":1,"quality_controlled":"1","abstract":[{"lang":"eng","text":"It is well known that cities increase air and surface temperatures compared to their rural surroundings, the so-called urban heat island (UHI) effect. However, the associated changes in atmospheric humidity (also known as urban dry island, UDI) and convection triggering remain largely unexplored and it is still unclear how urban modifications of the surface energy budget Influence the diurnal evolution of temperature and humidity in the Atmospheric Boundary Layer\r\n(ABL) and ultimately control the initiation of convective clouds.\r\nHere we quantify the impact of different urban settings and free atmospheric conditions on\r\nUHI, UDI, and convection triggers by means of a zero-order model of the ABL. Specifically, we\r\nderive an approximate solution for urban-rural changes in surface energy fluxes and ABL potential\r\ntemperature and humidity and we investigate the crossing between the ABL height and the lifting\r\ncondensation level (LCL) which is a proxy for the triggering of convective clouds. We show that\r\nurban areas are generally warmer and drier, thus causing an increase in both ABL and LCL\r\nheights. However, the response of the ABL-LCL crossing to surface conditions is non-linear and\r\nthere exists a range of free atmosphere conditions for which changes in imperviousness can\r\nimpact convective clouds."}],"title":"An analytical approximation of urban heat and dry islands and their impact on convection triggering","publisher":"Elsevier","publication_identifier":{"eissn":["2212-0955"]},"main_file_link":[{"open_access":"1","url":"https://doi.org/10.1016/j.uclim.2022.101346"}],"scopus_import":"1","intvolume":"        46","author":[{"last_name":"Chiu","full_name":"Chiu, Clinton T.F.","first_name":"Clinton T.F."},{"last_name":"Wang","full_name":"Wang, Kai","first_name":"Kai"},{"first_name":"Athanasios","last_name":"Paschalis","full_name":"Paschalis, Athanasios"},{"full_name":"Erfani, Tohid","last_name":"Erfani","first_name":"Tohid"},{"full_name":"Peleg, Nadav","last_name":"Peleg","first_name":"Nadav"},{"id":"cf8e546b-a9b0-11f0-a43b-aa89ed1b56d6","first_name":"Simone","full_name":"Fatichi, Simone","last_name":"Fatichi"},{"full_name":"Theeuwes, Natalie","last_name":"Theeuwes","first_name":"Natalie"},{"first_name":"Gabriele","last_name":"Manoli","full_name":"Manoli, Gabriele"}],"publication_status":"published","month":"12","volume":46,"language":[{"iso":"eng"}],"oa_version":"Published Version","das_tickbox":"1","extern":"1","OA_place":"publisher","citation":{"mla":"Chiu, Clinton T. F., et al. “An Analytical Approximation of Urban Heat and Dry Islands and Their Impact on Convection Triggering.” <i>Urban Climate</i>, vol. 46, 101346, Elsevier, 2022, doi:<a href=\"https://doi.org/10.1016/j.uclim.2022.101346\">10.1016/j.uclim.2022.101346</a>.","chicago":"Chiu, Clinton T.F., Kai Wang, Athanasios Paschalis, Tohid Erfani, Nadav Peleg, Simone Fatichi, Natalie Theeuwes, and Gabriele Manoli. “An Analytical Approximation of Urban Heat and Dry Islands and Their Impact on Convection Triggering.” <i>Urban Climate</i>. Elsevier, 2022. <a href=\"https://doi.org/10.1016/j.uclim.2022.101346\">https://doi.org/10.1016/j.uclim.2022.101346</a>.","ieee":"C. T. F. Chiu <i>et al.</i>, “An analytical approximation of urban heat and dry islands and their impact on convection triggering,” <i>Urban Climate</i>, vol. 46. Elsevier, 2022.","ista":"Chiu CTF, Wang K, Paschalis A, Erfani T, Peleg N, Fatichi S, Theeuwes N, Manoli G. 2022. An analytical approximation of urban heat and dry islands and their impact on convection triggering. Urban Climate. 46, 101346.","apa":"Chiu, C. T. F., Wang, K., Paschalis, A., Erfani, T., Peleg, N., Fatichi, S., … Manoli, G. (2022). An analytical approximation of urban heat and dry islands and their impact on convection triggering. <i>Urban Climate</i>. Elsevier. <a href=\"https://doi.org/10.1016/j.uclim.2022.101346\">https://doi.org/10.1016/j.uclim.2022.101346</a>","ama":"Chiu CTF, Wang K, Paschalis A, et al. An analytical approximation of urban heat and dry islands and their impact on convection triggering. <i>Urban Climate</i>. 2022;46. doi:<a href=\"https://doi.org/10.1016/j.uclim.2022.101346\">10.1016/j.uclim.2022.101346</a>","short":"C.T.F. Chiu, K. Wang, A. Paschalis, T. Erfani, N. Peleg, S. Fatichi, N. Theeuwes, G. Manoli, Urban Climate 46 (2022)."},"article_number":"101346","OA_type":"hybrid"},{"date_created":"2022-03-06T23:01:53Z","pmid":1,"external_id":{"pmid":["35183078"],"arxiv":["2111.12968"],"isi":["000796704500014"]},"_id":"10827","date_published":"2022-02-16T00:00:00Z","year":"2022","day":"16","article_processing_charge":"No","user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","type":"journal_article","publication":"The Journal of chemical physics","title":"High-pressure phase behaviors of titanium dioxide revealed by a Δ-learning potential","quality_controlled":"1","abstract":[{"lang":"eng","text":"Titanium dioxide has been extensively studied in the rutile or anatase phase, while its high-pressure phases are less well-understood, despite that many are thought to have interesting optical, mechanical, and electrochemical properties. First-principles methods, such as density functional theory (DFT), are often used to compute the enthalpies of TiO2 phases at 0 K, but they are expensive and, thus, impractical for long time scale and large system-size simulations at finite temperatures. On the other hand, cheap empirical potentials fail to capture the relative stabilities of various polymorphs. To model the thermodynamic behaviors of ambient and high-pressure phases of TiO2, we design an empirical model as a baseline and then train a machine learning potential based on the difference between the DFT data and the empirical model. This so-called Δ-learning potential contains long-range electrostatic interactions and predicts the 0 K enthalpies of stable TiO2 phases that are in good agreement with DFT. We construct a pressure–temperature phase diagram of TiO2 in the range 0 < P < 70 GPa and 100 < T < 1500 K. We then simulate dynamic phase transition processes by compressing anatase at different temperatures. At 300 K, we predominantly observe an anatase-to-baddeleyite transformation at about 20 GPa via a martensitic two-step mechanism with a highly ordered and collective atomic motion. At 2000 K, anatase can transform into cotunnite around 45–55 GPa in a thermally activated and probabilistic manner, accompanied by diffusive movement of oxygen atoms. The pressures computed for these transitions show good agreement with experiments. Our results shed light on how to synthesize and stabilize high-pressure TiO2 phases, and our method is generally applicable to other functional materials with multiple polymorphs."}],"publisher":"AIP Publishing","researchdata_availability":"yes","publication_identifier":{"eissn":["1089-7690"]},"main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/2111.12968"}],"arxiv":1,"status":"public","doi":"10.1063/5.0079844","date_updated":"2026-08-07T11:17:03Z","article_type":"original","dataavailabilitystatement":"All original data generated for the study and the Δ-learning potential for TiO2 constructed in this study are in the SI repository at https://github.com/jacobglee1/tio2-mlp.","oa":1,"language":[{"iso":"eng"}],"oa_version":"Preprint","scopus_import":"1","intvolume":"       156","acknowledgement":"J.G.L. and B.C. acknowledge the resources provided by the Cambridge Tier-2 system operated by the University of Cambridge Research Computing Service funded by the EPSRC Tier-2 capital (Grant No. EP/P020259/1).","author":[{"first_name":"Jacob G.","full_name":"Lee, Jacob G.","last_name":"Lee"},{"full_name":"Pickard, Chris J.","last_name":"Pickard","first_name":"Chris J."},{"first_name":"Bingqing","id":"cbe3cda4-d82c-11eb-8dc7-8ff94289fcc9","orcid":"0000-0002-3584-9632","last_name":"Cheng","full_name":"Cheng, Bingqing"}],"department":[{"_id":"BiCh"}],"publication_status":"published","isi":1,"month":"02","volume":156,"citation":{"short":"J.G. Lee, C.J. Pickard, B. Cheng, The Journal of Chemical Physics 156 (2022).","apa":"Lee, J. G., Pickard, C. J., &#38; Cheng, B. (2022). High-pressure phase behaviors of titanium dioxide revealed by a Δ-learning potential. <i>The Journal of Chemical Physics</i>. AIP Publishing. <a href=\"https://doi.org/10.1063/5.0079844\">https://doi.org/10.1063/5.0079844</a>","ama":"Lee JG, Pickard CJ, Cheng B. High-pressure phase behaviors of titanium dioxide revealed by a Δ-learning potential. <i>The Journal of chemical physics</i>. 2022;156(7). doi:<a href=\"https://doi.org/10.1063/5.0079844\">10.1063/5.0079844</a>","ista":"Lee JG, Pickard CJ, Cheng B. 2022. High-pressure phase behaviors of titanium dioxide revealed by a Δ-learning potential. The Journal of chemical physics. 156(7), 074106.","mla":"Lee, Jacob G., et al. “High-Pressure Phase Behaviors of Titanium Dioxide Revealed by a Δ-Learning Potential.” <i>The Journal of Chemical Physics</i>, vol. 156, no. 7, 074106, AIP Publishing, 2022, doi:<a href=\"https://doi.org/10.1063/5.0079844\">10.1063/5.0079844</a>.","chicago":"Lee, Jacob G., Chris J. Pickard, and Bingqing Cheng. “High-Pressure Phase Behaviors of Titanium Dioxide Revealed by a Δ-Learning Potential.” <i>The Journal of Chemical Physics</i>. AIP Publishing, 2022. <a href=\"https://doi.org/10.1063/5.0079844\">https://doi.org/10.1063/5.0079844</a>.","ieee":"J. G. Lee, C. J. Pickard, and B. Cheng, “High-pressure phase behaviors of titanium dioxide revealed by a Δ-learning potential,” <i>The Journal of chemical physics</i>, vol. 156, no. 7. AIP Publishing, 2022."},"article_number":"074106","corr_author":"1","issue":"7","supplementarymaterial":"yes","das_tickbox":"1"},{"date_updated":"2026-08-07T11:19:31Z","keyword":["Artificial Intelligence","Human-Computer Interaction","Software"],"status":"public","doi":"10.1088/2632-2153/ac4d11","oa":1,"article_type":"original","tmp":{"image":"/images/cc_by.png","short":"CC BY (4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)"},"dataavailabilitystatement":"The datasets used for this study are available at https://github.com/BingqingCheng/linear-regression-benchmarks. All data that support the findings of this study are included within the article (and any supplementary files).","file":[{"date_updated":"2023-01-23T10:42:04Z","success":1,"content_type":"application/pdf","file_id":"12343","checksum":"8930d4ad6ed9b47358c6f1a68666adb6","date_created":"2023-01-23T10:42:04Z","relation":"main_file","file_size":13814559,"access_level":"open_access","creator":"dernst","file_name":"2022_MachLearning_Poelking.pdf"}],"researchdata_availability":"yes","abstract":[{"text":"We introduce a machine-learning (ML) framework for high-throughput benchmarking of diverse representations of chemical systems against datasets of materials and molecules. The guiding principle underlying the benchmarking approach is to evaluate raw descriptor performance by limiting model complexity to simple regression schemes while enforcing best ML practices, allowing for unbiased hyperparameter optimization, and assessing learning progress through learning curves along series of synchronized train-test splits. The resulting models are intended as baselines that can inform future method development, in addition to indicating how easily a given dataset can be learnt. Through a comparative analysis of the training outcome across a diverse set of physicochemical, topological and geometric representations, we glean insight into the relative merits of these representations as well as their interrelatedness.","lang":"eng"}],"quality_controlled":"1","title":"BenchML: An extensible pipelining framework for benchmarking representations of materials and molecules at scale","publisher":"IOP Publishing","publication_identifier":{"issn":["2632-2153"]},"day":"17","article_processing_charge":"No","publication":"Machine Learning: Science and Technology","type":"journal_article","user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","external_id":{"isi":["000886534000001"]},"_id":"12128","date_published":"2022-11-17T00:00:00Z","date_created":"2023-01-12T12:02:21Z","file_date_updated":"2023-01-23T10:42:04Z","year":"2022","supplementarymaterial":"yes","das_tickbox":"1","related_material":{"link":[{"url":"https://github.com/capoe/benchml","relation":"software"}]},"has_accepted_license":"1","issue":"4","citation":{"short":"C. Poelking, F.A. Faber, B. Cheng, Machine Learning: Science and Technology 3 (2022).","ama":"Poelking C, Faber FA, Cheng B. BenchML: An extensible pipelining framework for benchmarking representations of materials and molecules at scale. <i>Machine Learning: Science and Technology</i>. 2022;3(4). doi:<a href=\"https://doi.org/10.1088/2632-2153/ac4d11\">10.1088/2632-2153/ac4d11</a>","apa":"Poelking, C., Faber, F. A., &#38; Cheng, B. (2022). BenchML: An extensible pipelining framework for benchmarking representations of materials and molecules at scale. <i>Machine Learning: Science and Technology</i>. IOP Publishing. <a href=\"https://doi.org/10.1088/2632-2153/ac4d11\">https://doi.org/10.1088/2632-2153/ac4d11</a>","ista":"Poelking C, Faber FA, Cheng B. 2022. BenchML: An extensible pipelining framework for benchmarking representations of materials and molecules at scale. Machine Learning: Science and Technology. 3(4), 040501.","ieee":"C. Poelking, F. A. Faber, and B. Cheng, “BenchML: An extensible pipelining framework for benchmarking representations of materials and molecules at scale,” <i>Machine Learning: Science and Technology</i>, vol. 3, no. 4. IOP Publishing, 2022.","chicago":"Poelking, Carl, Felix A Faber, and Bingqing Cheng. “BenchML: An Extensible Pipelining Framework for Benchmarking Representations of Materials and Molecules at Scale.” <i>Machine Learning: Science and Technology</i>. IOP Publishing, 2022. <a href=\"https://doi.org/10.1088/2632-2153/ac4d11\">https://doi.org/10.1088/2632-2153/ac4d11</a>.","mla":"Poelking, Carl, et al. “BenchML: An Extensible Pipelining Framework for Benchmarking Representations of Materials and Molecules at Scale.” <i>Machine Learning: Science and Technology</i>, vol. 3, no. 4, 040501, IOP Publishing, 2022, doi:<a href=\"https://doi.org/10.1088/2632-2153/ac4d11\">10.1088/2632-2153/ac4d11</a>."},"corr_author":"1","article_number":"040501","acknowledgement":"C P acknowledges funding from Astex through the Sustaining Innovation Program under the Milner Consortium. B C acknowledges resources provided by the Cambridge Tier-2 system operated by the University of Cambridge Research Computing Service funded by EPSRC Tier-2 capital Grant EP/P020259/1. F A F acknowledges funding from the Swiss National Science Foundation (Grant No. P2BSP2_191736). ","scopus_import":"1","intvolume":"         3","ddc":["000"],"month":"11","volume":3,"department":[{"_id":"BiCh"}],"author":[{"full_name":"Poelking, Carl","last_name":"Poelking","first_name":"Carl"},{"last_name":"Faber","full_name":"Faber, Felix A","first_name":"Felix A"},{"id":"cbe3cda4-d82c-11eb-8dc7-8ff94289fcc9","first_name":"Bingqing","orcid":"0000-0002-3584-9632","full_name":"Cheng, Bingqing","last_name":"Cheng"}],"publication_status":"published","isi":1,"oa_version":"Published Version","language":[{"iso":"eng"}]},{"issue":"12","article_number":"121101","corr_author":"1","citation":{"ama":"Cheng B. Computing chemical potentials of solutions from structure factors. <i>The Journal of Chemical Physics</i>. 2022;157(12). doi:<a href=\"https://doi.org/10.1063/5.0107059\">10.1063/5.0107059</a>","apa":"Cheng, B. (2022). Computing chemical potentials of solutions from structure factors. <i>The Journal of Chemical Physics</i>. AIP Publishing. <a href=\"https://doi.org/10.1063/5.0107059\">https://doi.org/10.1063/5.0107059</a>","short":"B. Cheng, The Journal of Chemical Physics 157 (2022).","chicago":"Cheng, Bingqing. “Computing Chemical Potentials of Solutions from Structure Factors.” <i>The Journal of Chemical Physics</i>. AIP Publishing, 2022. <a href=\"https://doi.org/10.1063/5.0107059\">https://doi.org/10.1063/5.0107059</a>.","ieee":"B. Cheng, “Computing chemical potentials of solutions from structure factors,” <i>The Journal of Chemical Physics</i>, vol. 157, no. 12. AIP Publishing, 2022.","mla":"Cheng, Bingqing. “Computing Chemical Potentials of Solutions from Structure Factors.” <i>The Journal of Chemical Physics</i>, vol. 157, no. 12, 121101, AIP Publishing, 2022, doi:<a href=\"https://doi.org/10.1063/5.0107059\">10.1063/5.0107059</a>.","ista":"Cheng B. 2022. Computing chemical potentials of solutions from structure factors. The Journal of Chemical Physics. 157(12), 121101."},"related_material":{"link":[{"url":"https://github.com/ BingqingCheng/S0","relation":"software"}]},"has_accepted_license":"1","das_tickbox":"1","supplementarymaterial":"yes","oa_version":"Published Version","language":[{"iso":"eng"}],"month":"09","volume":157,"publication_status":"published","isi":1,"author":[{"first_name":"Bingqing","id":"cbe3cda4-d82c-11eb-8dc7-8ff94289fcc9","orcid":"0000-0002-3584-9632","full_name":"Cheng, Bingqing","last_name":"Cheng"}],"department":[{"_id":"BiCh"}],"acknowledgement":"I thank Daan Frenkel for providing feedback on an early draft and for stimulating discussions, Debashish Mukherji and Robinson Cortes-Huerto for sharing the trajectories for urea–water mixtures, and Aleks Reinhardt for useful suggestions on the manuscript.","ddc":["530","540"],"intvolume":"       157","scopus_import":"1","publication_identifier":{"issn":["0021-9606"],"eissn":["1089-7690"]},"researchdata_availability":"yes","file":[{"checksum":"b0915b706568a663a9a372fca24adf35","file_id":"12441","content_type":"application/pdf","success":1,"date_updated":"2023-01-30T09:07:00Z","file_name":"2022_JourChemPhysics_Cheng.pdf","creator":"dernst","access_level":"open_access","file_size":4402384,"relation":"main_file","date_created":"2023-01-30T09:07:00Z"}],"publisher":"AIP Publishing","abstract":[{"lang":"eng","text":"The chemical potential of a component in a solution is defined as the free energy change as the amount of that component changes. Computing this fundamental thermodynamic property from atomistic simulations is notoriously difficult because of the convergence issues involved in free energy methods and finite size effects. This Communication presents the so-called S0 method, which can be used to obtain chemical potentials from static structure factors computed from equilibrium molecular dynamics simulations under the isothermal–isobaric ensemble. This new method is demonstrated on the systems of binary Lennard-Jones particles, urea–water mixtures, a NaCl aqueous solution, and a high-pressure carbon–hydrogen mixture. "}],"quality_controlled":"1","title":"Computing chemical potentials of solutions from structure factors","oa":1,"dataavailabilitystatement":"All PYTHON scripts and simulation input files generated for the study are in the SI repository https://github.com/BingqingCheng/S0, Ref. 29.\r\n29. B. Cheng, https://github.com/BingqingCheng/S0 “Data repository for the S0 method” (2020).","tmp":{"image":"/images/cc_by.png","short":"CC BY (4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)"},"article_type":"original","status":"public","date_updated":"2026-08-07T11:22:29Z","doi":"10.1063/5.0107059","keyword":["Physical and Theoretical Chemistry","General Physics and Astronomy"],"file_date_updated":"2023-01-30T09:07:00Z","year":"2022","date_published":"2022-09-30T00:00:00Z","external_id":{"isi":["000862856000003"],"pmid":["36182422"]},"_id":"12249","pmid":1,"date_created":"2023-01-16T09:56:20Z","publication":"The Journal of Chemical Physics","type":"journal_article","user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","article_processing_charge":"No","day":"30"},{"language":[{"iso":"eng"}],"oa_version":"Published Version","department":[{"_id":"BiCh"}],"author":[{"first_name":"Aleks","full_name":"Reinhardt, Aleks","last_name":"Reinhardt"},{"first_name":"Mandy","full_name":"Bethkenhagen, Mandy","last_name":"Bethkenhagen"},{"last_name":"Coppari","full_name":"Coppari, Federica","first_name":"Federica"},{"first_name":"Marius","last_name":"Millot","full_name":"Millot, Marius"},{"last_name":"Hamel","full_name":"Hamel, Sebastien","first_name":"Sebastien"},{"id":"cbe3cda4-d82c-11eb-8dc7-8ff94289fcc9","first_name":"Bingqing","orcid":"0000-0002-3584-9632","last_name":"Cheng","full_name":"Cheng, Bingqing"}],"publication_status":"published","isi":1,"volume":13,"month":"08","scopus_import":"1","intvolume":"        13","ddc":["540"],"acknowledgement":"We thank Chris Pickard for providing the initial structures of high-pressure ice phases and for useful advice. A.R. and B.C. acknowledge resources provided by the Cambridge Tier-2 system operated by the University of Cambridge Research Computing Service funded by EPSRC Tier-2 capital grant EP/P020259/1. M.B. was supported by the European Union within the Marie Skłodowska-Curie actions (xICE grant 894725) and acknowledges computational resources at North-German Supercomputing Alliance (HLRN) facilities. S.H. and M.M. acknowledge support from LDRD 19-ERD-031 and computing support from the Lawrence Livermore National Laboratory (LLNL) Institutional Computing Grand Challenge programme. F.C. acknowledges support from the US DOE Office of Science, Office of Fusion Energy Sciences. Lawrence Livermore National Laboratory is operated by Lawrence Livermore National Security, LLC, for the U.S. Department of Energy, National Nuclear Security Administration under Contract DE-AC52-07NA27344.","citation":{"short":"A. Reinhardt, M. Bethkenhagen, F. Coppari, M. Millot, S. Hamel, B. Cheng, Nature Communications 13 (2022).","apa":"Reinhardt, A., Bethkenhagen, M., Coppari, F., Millot, M., Hamel, S., &#38; Cheng, B. (2022). Thermodynamics of high-pressure ice phases explored with atomistic simulations. <i>Nature Communications</i>. Springer Nature. <a href=\"https://doi.org/10.1038/s41467-022-32374-1\">https://doi.org/10.1038/s41467-022-32374-1</a>","ama":"Reinhardt A, Bethkenhagen M, Coppari F, Millot M, Hamel S, Cheng B. Thermodynamics of high-pressure ice phases explored with atomistic simulations. <i>Nature Communications</i>. 2022;13. doi:<a href=\"https://doi.org/10.1038/s41467-022-32374-1\">10.1038/s41467-022-32374-1</a>","ista":"Reinhardt A, Bethkenhagen M, Coppari F, Millot M, Hamel S, Cheng B. 2022. Thermodynamics of high-pressure ice phases explored with atomistic simulations. Nature Communications. 13, 4707.","mla":"Reinhardt, Aleks, et al. “Thermodynamics of High-Pressure Ice Phases Explored with Atomistic Simulations.” <i>Nature Communications</i>, vol. 13, 4707, Springer Nature, 2022, doi:<a href=\"https://doi.org/10.1038/s41467-022-32374-1\">10.1038/s41467-022-32374-1</a>.","chicago":"Reinhardt, Aleks, Mandy Bethkenhagen, Federica Coppari, Marius Millot, Sebastien Hamel, and Bingqing Cheng. “Thermodynamics of High-Pressure Ice Phases Explored with Atomistic Simulations.” <i>Nature Communications</i>. Springer Nature, 2022. <a href=\"https://doi.org/10.1038/s41467-022-32374-1\">https://doi.org/10.1038/s41467-022-32374-1</a>.","ieee":"A. Reinhardt, M. Bethkenhagen, F. Coppari, M. Millot, S. Hamel, and B. Cheng, “Thermodynamics of high-pressure ice phases explored with atomistic simulations,” <i>Nature Communications</i>, vol. 13. Springer Nature, 2022."},"corr_author":"1","article_number":"4707","has_accepted_license":"1","das_tickbox":"1","supplementarymaterial":"yes","year":"2022","file_date_updated":"2022-08-22T06:33:02Z","pmid":1,"date_created":"2022-08-21T22:01:55Z","external_id":{"isi":["000838655300022"],"pmid":["35948550"]},"_id":"11937","date_published":"2022-08-10T00:00:00Z","type":"journal_article","user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","publication":"Nature Communications","day":"10","article_processing_charge":"No","publication_identifier":{"eissn":["2041-1723"]},"quality_controlled":"1","title":"Thermodynamics of high-pressure ice phases explored with atomistic simulations","abstract":[{"text":"Most experimentally known high-pressure ice phases have a body-centred cubic (bcc) oxygen lattice. Our large-scale molecular-dynamics simulations with a machine-learning potential indicate that, amongst these bcc ice phases, ices VII, VII′ and X are the same thermodynamic phase under different conditions, whereas superionic ice VII″ has a first-order phase boundary with ice VII′. Moreover, at about 300 GPa, the transformation between ice X and the Pbcm phase has a sharp structural change but no apparent activation barrier, whilst at higher pressures the barrier gradually increases. Our study thus clarifies the phase behaviour of the high-pressure ices and reveals peculiar solid–solid transition mechanisms not known in other systems.","lang":"eng"}],"publisher":"Springer Nature","file":[{"date_created":"2022-08-22T06:33:02Z","relation":"main_file","file_size":1767206,"creator":"dernst","access_level":"open_access","file_name":"2022_NatureCommunications_Reinhardt.pdf","date_updated":"2022-08-22T06:33:02Z","success":1,"content_type":"application/pdf","checksum":"8ff9b689cde59fd3a9959a9f01929dea","file_id":"11939"}],"researchdata_availability":"yes","tmp":{"image":"/images/cc_by.png","short":"CC BY (4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)"},"article_type":"original","dataavailabilitystatement":"All original data generated for the study are in the SI repository https://github.com/BingqingCheng/highP-ice.","oa":1,"status":"public","doi":"10.1038/s41467-022-32374-1","date_updated":"2026-08-07T11:18:25Z"},{"scopus_import":"1","intvolume":"         1","ddc":["000"],"acknowledgement":"A.G., C.Z., and A.L. gratefully acknowledge support from the European Union’s Horizon 2020 research and innovation program (grant number 824143, MaX ’Materials design at the eXascale’ Centre of Excellence). The authors would like to thank M. Carli, D. Doimo, and I. Macocco (SISSA) for the discussions, M. Caro (Aalto University) for the precious help in using the TurboGap code, and D. Frenkel (University of Cambridge) and N. Bernstein (US Naval Research Laboratory) for useful feedback on the manuscript.\r\nThis work is supported in part by funds from the European Union’s Horizon 2020 research and innovation program (grant number 824143, MaX ’Materials design at the eXascale’ Centre of Excellence).","department":[{"_id":"BiCh"}],"author":[{"first_name":"Aldo","last_name":"Glielmo","full_name":"Glielmo, Aldo"},{"first_name":"Claudio","full_name":"Zeni, Claudio","last_name":"Zeni"},{"id":"cbe3cda4-d82c-11eb-8dc7-8ff94289fcc9","first_name":"Bingqing","orcid":"0000-0002-3584-9632","last_name":"Cheng","full_name":"Cheng, Bingqing"},{"last_name":"Csanyi","full_name":"Csanyi, Gabor","first_name":"Gabor"},{"first_name":"Alessandro","last_name":"Laio","full_name":"Laio, Alessandro"}],"publication_status":"published","month":"05","volume":1,"language":[{"iso":"eng"}],"oa_version":"Published Version","supplementarymaterial":"yes","das_tickbox":"1","has_accepted_license":"1","citation":{"ieee":"A. Glielmo, C. Zeni, B. Cheng, G. Csanyi, and A. Laio, “Ranking the information content of distance measures,” <i>PNAS Nexus</i>, vol. 1, no. 2. Oxford University Press, 2022.","chicago":"Glielmo, Aldo, Claudio Zeni, Bingqing Cheng, Gabor Csanyi, and Alessandro Laio. “Ranking the Information Content of Distance Measures.” <i>PNAS Nexus</i>. Oxford University Press, 2022. <a href=\"https://doi.org/10.1093/pnasnexus/pgac039\">https://doi.org/10.1093/pnasnexus/pgac039</a>.","mla":"Glielmo, Aldo, et al. “Ranking the Information Content of Distance Measures.” <i>PNAS Nexus</i>, vol. 1, no. 2, pgac039, Oxford University Press, 2022, doi:<a href=\"https://doi.org/10.1093/pnasnexus/pgac039\">10.1093/pnasnexus/pgac039</a>.","ista":"Glielmo A, Zeni C, Cheng B, Csanyi G, Laio A. 2022. Ranking the information content of distance measures. PNAS Nexus. 1(2), pgac039.","ama":"Glielmo A, Zeni C, Cheng B, Csanyi G, Laio A. Ranking the information content of distance measures. <i>PNAS Nexus</i>. 2022;1(2). doi:<a href=\"https://doi.org/10.1093/pnasnexus/pgac039\">10.1093/pnasnexus/pgac039</a>","apa":"Glielmo, A., Zeni, C., Cheng, B., Csanyi, G., &#38; Laio, A. (2022). Ranking the information content of distance measures. <i>PNAS Nexus</i>. Oxford University Press. <a href=\"https://doi.org/10.1093/pnasnexus/pgac039\">https://doi.org/10.1093/pnasnexus/pgac039</a>","short":"A. Glielmo, C. Zeni, B. Cheng, G. Csanyi, A. Laio, PNAS Nexus 1 (2022)."},"article_number":"pgac039","issue":"2","day":"01","article_processing_charge":"Yes","type":"journal_article","user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","publication":"PNAS Nexus","pmid":1,"date_created":"2021-07-20T06:31:53Z","external_id":{"arxiv":["2104.15079"],"pmid":["36713323"]},"_id":"9695","date_published":"2022-05-01T00:00:00Z","year":"2022","file_date_updated":"2024-05-29T06:21:33Z","arxiv":1,"doi":"10.1093/pnasnexus/pgac039","date_updated":"2026-08-07T11:23:54Z","status":"public","article_type":"original","tmp":{"short":"CC BY-NC-ND (4.0)","image":"/images/cc_by_nc_nd.png","name":"Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)","legal_code_url":"https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode"},"dataavailabilitystatement":"Details on the datasets used are available in the supplementary material.","oa":1,"quality_controlled":"1","abstract":[{"lang":"eng","text":"Real-world data typically contain a large number of features that are often heterogeneous in nature, relevance, and also units of measure. When assessing the similarity between data points, one can build various distance measures using subsets of these features. Using the fewest features but still retaining sufficient information about the system is crucial in many statistical learning approaches, particularly when data are sparse. We introduce a statistical test that can assess the relative information retained when using two different distance measures, and determine if they are equivalent, independent, or if one is more informative than the other. This in turn allows finding the most informative distance measure out of a pool of candidates. The approach is applied to find the most relevant policy variables for controlling the Covid-19 epidemic and to find compact yet informative representations of atomic structures, but its potential applications are wide ranging in many branches of science."}],"title":"Ranking the information content of distance measures","publisher":"Oxford University Press","researchdata_availability":"no","file":[{"content_type":"application/pdf","checksum":"f6552854d760eb574ce97abce2c8ef89","file_id":"17080","success":1,"date_updated":"2024-05-29T06:21:33Z","file_name":"2022_PNASNexus_Glielmo.pdf","creator":"dernst","access_level":"open_access","file_size":2005167,"relation":"main_file","date_created":"2024-05-29T06:21:33Z"}],"publication_identifier":{"eissn":["2752-6542"]}},{"_id":"12237","external_id":{"isi":["000917837600001"],"pmid":["36248227"]},"date_published":"2022-09-20T00:00:00Z","date_created":"2023-01-16T09:51:26Z","pmid":1,"file_date_updated":"2023-01-30T07:35:09Z","year":"2022","day":"20","article_processing_charge":"Yes (via OA deal)","publication":"Chemistry of Materials","type":"journal_article","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","file":[{"date_updated":"2023-01-30T07:35:09Z","content_type":"application/pdf","file_id":"12434","checksum":"f7143e44ab510519d1949099c3558532","success":1,"file_size":10923495,"creator":"dernst","access_level":"open_access","relation":"main_file","date_created":"2023-01-30T07:35:09Z","file_name":"2022_ChemistryMaterials_Fiedler.pdf"}],"quality_controlled":"1","title":"Solution-processed inorganic thermoelectric materials: Opportunities and challenges ∇","abstract":[{"text":"Thermoelectric technology requires synthesizing complex materials where not only the crystal structure but also other structural features such as defects, grain size and orientation, and interfaces must be controlled. To date, conventional solid-state techniques are unable to provide this level of control. Herein, we present a synthetic approach in which dense inorganic thermoelectric materials are produced by the consolidation of well-defined nanoparticle powders. The idea is that controlling the characteristics of the powder allows the chemical transformations that take place during consolidation to be guided, ultimately yielding inorganic solids with targeted features. Different from conventional methods, syntheses in solution can produce particles with unprecedented control over their size, shape, crystal structure, composition, and surface chemistry. However, to date, most works have focused only on the low-cost benefits of this strategy. In this perspective, we first cover the opportunities that solution processing of the powder offers, emphasizing the potential structural features that can be controlled by precisely engineering the inorganic core of the particle, the surface, and the organization of the particles before consolidation. We then discuss the challenges of this synthetic approach and more practical matters related to solution processing. Finally, we suggest some good practices for adequate knowledge transfer and improving reproducibility among different laboratories.","lang":"eng"}],"publisher":"American Chemical Society","publication_identifier":{"eissn":["1520-5002"],"issn":["0897-4756"]},"doi":"10.1021/acs.chemmater.2c01967","status":"public","keyword":["Materials Chemistry","General Chemical Engineering","General Chemistry"],"date_updated":"2026-08-11T12:39:14Z","project":[{"call_identifier":"H2020","_id":"2564DBCA-B435-11E9-9278-68D0E5697425","name":"International IST Doctoral Program","grant_number":"665385"}],"oa":1,"article_type":"original","tmp":{"image":"/images/cc_by.png","short":"CC BY (4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)"},"oa_version":"Published Version","page":"8471-8489","language":[{"iso":"eng"}],"acknowledgement":"This work was financially supported by ISTA and the Werner Siemens Foundation. M.C. has received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie Grant Agreement no. 665385.","scopus_import":"1","intvolume":"        34","ddc":["540"],"month":"09","volume":34,"author":[{"last_name":"Fiedler","full_name":"Fiedler, Christine","id":"bd3fceba-dc74-11ea-a0a7-c17f71817366","first_name":"Christine"},{"full_name":"Kleinhanns, Tobias","last_name":"Kleinhanns","orcid":"0000-0003-1537-7436","id":"8BD9DE16-AB3C-11E9-9C8C-2A03E6697425","first_name":"Tobias"},{"id":"6e5c50b8-97dc-11ed-be98-b0a74c84cae0","first_name":"Maria","full_name":"Garcia, Maria","last_name":"Garcia"},{"orcid":"0000-0002-6962-8598","last_name":"Lee","full_name":"Lee, Seungho","first_name":"Seungho","id":"BB243B88-D767-11E9-B658-BC13E6697425"},{"first_name":"Mariano","id":"45D7531A-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0003-4566-5877","full_name":"Calcabrini, Mariano","last_name":"Calcabrini"},{"orcid":"0000-0001-5013-2843","full_name":"Ibáñez, Maria","last_name":"Ibáñez","first_name":"Maria","id":"43C61214-F248-11E8-B48F-1D18A9856A87"}],"department":[{"_id":"MaIb"}],"isi":1,"publication_status":"published","related_material":{"record":[{"relation":"dissertation_contains","id":"20415","status":"public"},{"relation":"dissertation_contains","status":"public","id":"12885"},{"id":"22017","status":"public","relation":"dissertation_contains"},{"id":"22626","status":"public","relation":"dissertation_contains"}]},"ec_funded":1,"has_accepted_license":"1","issue":"19","citation":{"short":"C. Fiedler, T. Kleinhanns, M. Garcia, S. Lee, M. Calcabrini, M. Ibáñez, Chemistry of Materials 34 (2022) 8471–8489.","apa":"Fiedler, C., Kleinhanns, T., Garcia, M., Lee, S., Calcabrini, M., &#38; Ibáñez, M. (2022). Solution-processed inorganic thermoelectric materials: Opportunities and challenges ∇. <i>Chemistry of Materials</i>. American Chemical Society. <a href=\"https://doi.org/10.1021/acs.chemmater.2c01967\">https://doi.org/10.1021/acs.chemmater.2c01967</a>","ama":"Fiedler C, Kleinhanns T, Garcia M, Lee S, Calcabrini M, Ibáñez M. Solution-processed inorganic thermoelectric materials: Opportunities and challenges ∇. <i>Chemistry of Materials</i>. 2022;34(19):8471-8489. doi:<a href=\"https://doi.org/10.1021/acs.chemmater.2c01967\">10.1021/acs.chemmater.2c01967</a>","ista":"Fiedler C, Kleinhanns T, Garcia M, Lee S, Calcabrini M, Ibáñez M. 2022. Solution-processed inorganic thermoelectric materials: Opportunities and challenges ∇. Chemistry of Materials. 34(19), 8471–8489.","mla":"Fiedler, Christine, et al. “Solution-Processed Inorganic Thermoelectric Materials: Opportunities and Challenges ∇.” <i>Chemistry of Materials</i>, vol. 34, no. 19, American Chemical Society, 2022, pp. 8471–89, doi:<a href=\"https://doi.org/10.1021/acs.chemmater.2c01967\">10.1021/acs.chemmater.2c01967</a>.","chicago":"Fiedler, Christine, Tobias Kleinhanns, Maria Garcia, Seungho Lee, Mariano Calcabrini, and Maria Ibáñez. “Solution-Processed Inorganic Thermoelectric Materials: Opportunities and Challenges ∇.” <i>Chemistry of Materials</i>. American Chemical Society, 2022. <a href=\"https://doi.org/10.1021/acs.chemmater.2c01967\">https://doi.org/10.1021/acs.chemmater.2c01967</a>.","ieee":"C. Fiedler, T. Kleinhanns, M. Garcia, S. Lee, M. Calcabrini, and M. Ibáñez, “Solution-processed inorganic thermoelectric materials: Opportunities and challenges ∇,” <i>Chemistry of Materials</i>, vol. 34, no. 19. American Chemical Society, pp. 8471–8489, 2022."},"corr_author":"1"},{"ec_funded":1,"issue":"5","citation":{"ista":"Erbar M, Forkert DL, Maas J, Mugnolo D. 2022. Gradient flow formulation of diffusion equations in the Wasserstein space over a metric graph. Networks and Heterogeneous Media. 17(5), 687–717.","chicago":"Erbar, Matthias, Dominik L Forkert, Jan Maas, and Delio Mugnolo. “Gradient Flow Formulation of Diffusion Equations in the Wasserstein Space over a Metric Graph.” <i>Networks and Heterogeneous Media</i>. AIMS, 2022. <a href=\"https://doi.org/10.3934/nhm.2022023\">https://doi.org/10.3934/nhm.2022023</a>.","ieee":"M. Erbar, D. L. Forkert, J. Maas, and D. Mugnolo, “Gradient flow formulation of diffusion equations in the Wasserstein space over a metric graph,” <i>Networks and Heterogeneous Media</i>, vol. 17, no. 5. AIMS, pp. 687–717, 2022.","mla":"Erbar, Matthias, et al. “Gradient Flow Formulation of Diffusion Equations in the Wasserstein Space over a Metric Graph.” <i>Networks and Heterogeneous Media</i>, vol. 17, no. 5, AIMS, 2022, pp. 687–717, doi:<a href=\"https://doi.org/10.3934/nhm.2022023\">10.3934/nhm.2022023</a>.","short":"M. Erbar, D.L. Forkert, J. Maas, D. Mugnolo, Networks and Heterogeneous Media 17 (2022) 687–717.","ama":"Erbar M, Forkert DL, Maas J, Mugnolo D. Gradient flow formulation of diffusion equations in the Wasserstein space over a metric graph. <i>Networks and Heterogeneous Media</i>. 2022;17(5):687-717. doi:<a href=\"https://doi.org/10.3934/nhm.2022023\">10.3934/nhm.2022023</a>","apa":"Erbar, M., Forkert, D. L., Maas, J., &#38; Mugnolo, D. (2022). Gradient flow formulation of diffusion equations in the Wasserstein space over a metric graph. <i>Networks and Heterogeneous Media</i>. AIMS. <a href=\"https://doi.org/10.3934/nhm.2022023\">https://doi.org/10.3934/nhm.2022023</a>"},"corr_author":"1","oa_version":"Preprint","page":"687-717","language":[{"iso":"eng"}],"acknowledgement":"ME acknowledges funding by the Deutsche Forschungsgemeinschaft (DFG), Grant SFB 1283/2 2021 – 317210226. DF and JM were supported by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 716117). JM also acknowledges support by the Austrian Science Fund (FWF), Project SFB F65. The work of DM was partially supported by the Deutsche Forschungsgemeinschaft\r\n(DFG), Grant 397230547. This article is based upon work from COST Action\r\n18232 MAT-DYN-NET, supported by COST (European Cooperation in Science\r\nand Technology), www.cost.eu. We wish to thank Martin Burger and Jan-Frederik\r\nPietschmann for useful discussions. We are grateful to the anonymous referees for\r\ntheir careful reading and useful suggestions.","scopus_import":"1","intvolume":"        17","volume":17,"month":"10","department":[{"_id":"JaMa"}],"author":[{"last_name":"Erbar","full_name":"Erbar, Matthias","first_name":"Matthias"},{"full_name":"Forkert, Dominik L","last_name":"Forkert","first_name":"Dominik L","id":"35C79D68-F248-11E8-B48F-1D18A9856A87"},{"first_name":"Jan","id":"4C5696CE-F248-11E8-B48F-1D18A9856A87","last_name":"Maas","full_name":"Maas, Jan","orcid":"0000-0002-0845-1338"},{"last_name":"Mugnolo","full_name":"Mugnolo, Delio","first_name":"Delio"}],"isi":1,"publication_status":"published","title":"Gradient flow formulation of diffusion equations in the Wasserstein space over a metric graph","quality_controlled":"1","abstract":[{"lang":"eng","text":"This paper contains two contributions in the study of optimal transport on metric graphs. Firstly, we prove a Benamou–Brenier formula for the Wasserstein distance, which establishes the equivalence of static and dynamical optimal transport. Secondly, in the spirit of Jordan–Kinderlehrer–Otto, we show that McKean–Vlasov equations can be formulated as gradient flow of the free energy in the Wasserstein space of probability measures. The proofs of these results are based on careful regularisation arguments to circumvent some of the difficulties arising in metric graphs, namely, branching of geodesics and the failure of semi-convexity of entropy functionals in the Wasserstein space."}],"publisher":"AIMS","main_file_link":[{"open_access":"1","url":"https://doi.org/10.48550/arXiv.2105.05677"}],"publication_identifier":{"issn":["1556-1801"],"eissn":["1556-181X"]},"date_updated":"2026-08-12T06:20:30Z","status":"public","doi":"10.3934/nhm.2022023","project":[{"call_identifier":"H2020","_id":"256E75B8-B435-11E9-9278-68D0E5697425","name":"Optimal Transport and Stochastic Dynamics","grant_number":"716117"},{"name":"Taming Complexity in Partial Differential Systems","grant_number":"F6504","_id":"fc31cba2-9c52-11eb-aca3-ff467d239cd2"}],"arxiv":1,"oa":1,"article_type":"original","external_id":{"arxiv":["2105.05677"],"isi":["000812422100001"]},"_id":"11700","date_published":"2022-10-01T00:00:00Z","date_created":"2022-07-31T22:01:46Z","year":"2022","day":"01","article_processing_charge":"No","publication":"Networks and Heterogeneous Media","type":"journal_article","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87"},{"corr_author":"1","citation":{"ista":"Iofinova EB, Krumes A, Kurtz M, Alistarh D-A. 2022. How well do sparse ImageNet models transfer? 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition. CVPR: Computer Vision and Pattern Recognition, 12256–12266.","mla":"Iofinova, Eugenia B., et al. “How Well Do Sparse ImageNet Models Transfer?” <i>2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition</i>, IEEE, 2022, pp. 12256–66, doi:<a href=\"https://doi.org/10.1109/cvpr52688.2022.01195\">10.1109/cvpr52688.2022.01195</a>.","ieee":"E. B. Iofinova, A. Krumes, M. Kurtz, and D.-A. Alistarh, “How well do sparse ImageNet models transfer?,” in <i>2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition</i>, New Orleans, LA, United States, 2022, pp. 12256–12266.","chicago":"Iofinova, Eugenia B, Alexandra Krumes, Mark Kurtz, and Dan-Adrian Alistarh. “How Well Do Sparse ImageNet Models Transfer?” In <i>2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition</i>, 12256–66. IEEE, 2022. <a href=\"https://doi.org/10.1109/cvpr52688.2022.01195\">https://doi.org/10.1109/cvpr52688.2022.01195</a>.","short":"E.B. Iofinova, A. Krumes, M. Kurtz, D.-A. Alistarh, in:, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition, IEEE, 2022, pp. 12256–12266.","apa":"Iofinova, E. B., Krumes, A., Kurtz, M., &#38; Alistarh, D.-A. (2022). How well do sparse ImageNet models transfer? In <i>2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition</i> (pp. 12256–12266). New Orleans, LA, United States: IEEE. <a href=\"https://doi.org/10.1109/cvpr52688.2022.01195\">https://doi.org/10.1109/cvpr52688.2022.01195</a>","ama":"Iofinova EB, Krumes A, Kurtz M, Alistarh D-A. How well do sparse ImageNet models transfer? In: <i>2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition</i>. IEEE; 2022:12256-12266. doi:<a href=\"https://doi.org/10.1109/cvpr52688.2022.01195\">10.1109/cvpr52688.2022.01195</a>"},"ec_funded":1,"related_material":{"record":[{"relation":"dissertation_contains","id":"13074","status":"public"}]},"isi":1,"publication_status":"published","department":[{"_id":"DaAl"},{"_id":"ChLa"}],"author":[{"first_name":"Eugenia B","id":"f9a17499-f6e0-11ea-865d-fdf9a3f77117","last_name":"Iofinova","full_name":"Iofinova, Eugenia B","orcid":"0000-0002-7778-3221"},{"first_name":"Elena-Alexandra","id":"32D78294-F248-11E8-B48F-1D18A9856A87","full_name":"Peste, Elena-Alexandra","last_name":"Peste"},{"first_name":"Mark","full_name":"Kurtz, Mark","last_name":"Kurtz"},{"orcid":"0000-0003-3650-940X","full_name":"Alistarh, Dan-Adrian","last_name":"Alistarh","id":"4A899BFC-F248-11E8-B48F-1D18A9856A87","first_name":"Dan-Adrian"}],"conference":{"name":"CVPR: Computer Vision and Pattern Recognition","start_date":"2022-06-18","location":"New Orleans, LA, United States","end_date":"2022-06-24"},"month":"09","scopus_import":"1","acknowledgement":"he authors would like to sincerely thank Christoph Lampert and Nir Shavit for fruitful discussions during the development of this work, and Eldar Kurtic for experimental support. EI was supported in part by the FWF DK VGSCO, grant agreement number W1260-N35, while AP and DA acknowledge generous support by the ERC, via Starting Grant 805223 ScaleML.","language":[{"iso":"eng"}],"page":"12256-12266","oa_version":"Preprint","oa":1,"arxiv":1,"project":[{"grant_number":"W1260-N35","name":"Vienna Graduate School on Computational Optimization","_id":"9B9290DE-BA93-11EA-9121-9846C619BF3A"},{"_id":"268A44D6-B435-11E9-9278-68D0E5697425","grant_number":"805223","name":"Elastic Coordination for Scalable Machine Learning","call_identifier":"H2020"}],"status":"public","doi":"10.1109/cvpr52688.2022.01195","date_updated":"2026-08-12T06:34:08Z","publication_identifier":{"eissn":["2575-7075"]},"main_file_link":[{"open_access":"1","url":"https://doi.org/10.48550/arXiv.2111.13445"}],"publisher":"IEEE","quality_controlled":"1","title":"How well do sparse ImageNet models transfer?","abstract":[{"lang":"eng","text":"Transfer learning is a classic paradigm by which models pretrained on large “upstream” datasets are adapted to yield good results on “downstream” specialized datasets. Generally, more accurate models on the “upstream” dataset tend to provide better transfer accuracy “downstream”. In this work, we perform an in-depth investigation of this phenomenon in the context of convolutional neural networks (CNNs) trained on the ImageNet dataset, which have been pruned-that is, compressed by sparsifiying their connections. We consider transfer using unstructured pruned models obtained by applying several state-of-the-art pruning methods, including magnitude-based, second-order, regrowth, lottery-ticket, and regularization approaches, in the context of twelve standard transfer tasks. In a nutshell, our study shows that sparse models can match or even outperform the transfer performance of dense models, even at high sparsities, and, while doing so, can lead to significant inference and even training speedups. At the same time, we observe and analyze significant differences in the behaviour of different pruning methods. The code is available at: https://github.com/IST-DASLab/sparse-imagenet-transfer."}],"type":"conference","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","publication":"2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition","article_processing_charge":"No","day":"27","year":"2022","date_created":"2023-01-16T10:06:00Z","date_published":"2022-09-27T00:00:00Z","external_id":{"isi":["000870759105034"],"arxiv":["2111.13445"]},"_id":"12299"},{"corr_author":"1","citation":{"ista":"Tomaszewska P, Lampert C. 2022. Lightweight conditional model extrapolation for streaming data under class-prior shift. 26th International Conference on Pattern Recognition. ICPR: International Conference on Pattern Recognition vol. 2022, 2128–2134.","mla":"Tomaszewska, Paulina, and Christoph Lampert. “Lightweight Conditional Model Extrapolation for Streaming Data under Class-Prior Shift.” <i>26th International Conference on Pattern Recognition</i>, vol. 2022, IEEE, 2022, pp. 2128–34, doi:<a href=\"https://doi.org/10.1109/icpr56361.2022.9956195\">10.1109/icpr56361.2022.9956195</a>.","ieee":"P. Tomaszewska and C. Lampert, “Lightweight conditional model extrapolation for streaming data under class-prior shift,” in <i>26th International Conference on Pattern Recognition</i>, Montreal, Canada, 2022, vol. 2022, pp. 2128–2134.","chicago":"Tomaszewska, Paulina, and Christoph Lampert. “Lightweight Conditional Model Extrapolation for Streaming Data under Class-Prior Shift.” In <i>26th International Conference on Pattern Recognition</i>, 2022:2128–34. IEEE, 2022. <a href=\"https://doi.org/10.1109/icpr56361.2022.9956195\">https://doi.org/10.1109/icpr56361.2022.9956195</a>.","short":"P. Tomaszewska, C. Lampert, in:, 26th International Conference on Pattern Recognition, IEEE, 2022, pp. 2128–2134.","apa":"Tomaszewska, P., &#38; Lampert, C. (2022). Lightweight conditional model extrapolation for streaming data under class-prior shift. In <i>26th International Conference on Pattern Recognition</i> (Vol. 2022, pp. 2128–2134). Montreal, Canada: IEEE. <a href=\"https://doi.org/10.1109/icpr56361.2022.9956195\">https://doi.org/10.1109/icpr56361.2022.9956195</a>","ama":"Tomaszewska P, Lampert C. Lightweight conditional model extrapolation for streaming data under class-prior shift. In: <i>26th International Conference on Pattern Recognition</i>. Vol 2022. IEEE; 2022:2128-2134. doi:<a href=\"https://doi.org/10.1109/icpr56361.2022.9956195\">10.1109/icpr56361.2022.9956195</a>"},"intvolume":"      2022","scopus_import":"1","publication_status":"published","isi":1,"department":[{"_id":"ChLa"}],"conference":{"location":"Montreal, Canada","start_date":"2022-08-21","end_date":"2022-08-25","name":"ICPR: International Conference on Pattern Recognition"},"author":[{"last_name":"Tomaszewska","full_name":"Tomaszewska, Paulina","first_name":"Paulina"},{"first_name":"Christoph","id":"40C20FD2-F248-11E8-B48F-1D18A9856A87","last_name":"Lampert","full_name":"Lampert, Christoph","orcid":"0000-0001-8622-7887"}],"volume":2022,"month":"11","language":[{"iso":"eng"}],"page":"2128-2134","oa_version":"Preprint","arxiv":1,"doi":"10.1109/icpr56361.2022.9956195","status":"public","date_updated":"2026-08-12T06:35:14Z","oa":1,"publisher":"IEEE","title":"Lightweight conditional model extrapolation for streaming data under class-prior shift","quality_controlled":"1","abstract":[{"text":"We introduce LIMES, a new method for learning with non-stationary streaming data, inspired by the recent success of meta-learning. The main idea is not to attempt to learn a single classifier that would have to work well across all occurring data distributions, nor many separate classifiers, but to exploit a hybrid strategy: we learn a single set of model parameters from which a specific classifier for any specific data distribution is derived via classifier adaptation. Assuming a multiclass classification setting with class-prior shift, the adaptation step can be performed analytically with only the classifier’s bias terms being affected. Another contribution of our work is an extrapolation step that predicts suitable adaptation parameters for future time steps based on the previous data. In combination, we obtain a lightweight procedure for learning from streaming data with varying class distribution that adds no trainable parameters and almost no memory or computational overhead compared to training a single model. Experiments on a set of exemplary tasks using Twitter data show that LIMES achieves higher accuracy than alternative approaches, especially with respect to the relevant real-world metric of lowest within-day accuracy.","lang":"eng"}],"publication_identifier":{"eisbn":["9781665490627"],"eissn":["2831-7475"]},"main_file_link":[{"url":"https://doi.org/10.48550/arXiv.2206.05181","open_access":"1"}],"article_processing_charge":"No","day":"29","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","type":"conference","publication":"26th International Conference on Pattern Recognition","date_created":"2023-01-12T12:09:38Z","date_published":"2022-11-29T00:00:00Z","external_id":{"isi":["000897707602018"],"arxiv":["2206.05181"]},"_id":"12161","year":"2022"},{"conference":{"name":"ICDCSW: International Conference on Distributed Computing Systems Workshop","end_date":"2022-07-10","location":"Bologna, Italy","start_date":"2022-07-10"},"department":[{"_id":"ElKo"}],"author":[{"first_name":"Alfonso","last_name":"De la Rocha","full_name":"De la Rocha, Alfonso"},{"first_name":"Eleftherios","id":"f5983044-d7ef-11ea-ac6d-fd1430a26d30","orcid":"0000-0002-8827-3382","last_name":"Kokoris Kogias","full_name":"Kokoris Kogias, Eleftherios"},{"first_name":"Jorge M.","full_name":"Soares, Jorge M.","last_name":"Soares"},{"first_name":"Marko","full_name":"Vukolic, Marko","last_name":"Vukolic"}],"isi":1,"publication_status":"published","volume":2022,"month":"11","scopus_import":"1","intvolume":"      2022","language":[{"iso":"eng"}],"oa_version":"None","page":"45-52","citation":{"short":"A. De la Rocha, E. Kokoris Kogias, J.M. Soares, M. Vukolic, in:, 42nd International Conference on Distributed Computing Systems Workshops, IEEE, 2022, pp. 45–52.","ama":"De la Rocha A, Kokoris Kogias E, Soares JM, Vukolic M. Hierarchical consensus: A horizontal scaling framework for blockchains. In: <i>42nd International Conference on Distributed Computing Systems Workshops</i>. Vol 2022. IEEE; 2022:45-52. doi:<a href=\"https://doi.org/10.1109/icdcsw56584.2022.00018\">10.1109/icdcsw56584.2022.00018</a>","apa":"De la Rocha, A., Kokoris Kogias, E., Soares, J. M., &#38; Vukolic, M. (2022). Hierarchical consensus: A horizontal scaling framework for blockchains. In <i>42nd International Conference on Distributed Computing Systems Workshops</i> (Vol. 2022, pp. 45–52). Bologna, Italy: IEEE. <a href=\"https://doi.org/10.1109/icdcsw56584.2022.00018\">https://doi.org/10.1109/icdcsw56584.2022.00018</a>","ista":"De la Rocha A, Kokoris Kogias E, Soares JM, Vukolic M. 2022. Hierarchical consensus: A horizontal scaling framework for blockchains. 42nd International Conference on Distributed Computing Systems Workshops. ICDCSW: International Conference on Distributed Computing Systems Workshop vol. 2022, 45–52.","ieee":"A. De la Rocha, E. Kokoris Kogias, J. M. Soares, and M. Vukolic, “Hierarchical consensus: A horizontal scaling framework for blockchains,” in <i>42nd International Conference on Distributed Computing Systems Workshops</i>, Bologna, Italy, 2022, vol. 2022, pp. 45–52.","chicago":"De la Rocha, Alfonso, Eleftherios Kokoris Kogias, Jorge M. Soares, and Marko Vukolic. “Hierarchical Consensus: A Horizontal Scaling Framework for Blockchains.” In <i>42nd International Conference on Distributed Computing Systems Workshops</i>, 2022:45–52. IEEE, 2022. <a href=\"https://doi.org/10.1109/icdcsw56584.2022.00018\">https://doi.org/10.1109/icdcsw56584.2022.00018</a>.","mla":"De la Rocha, Alfonso, et al. “Hierarchical Consensus: A Horizontal Scaling Framework for Blockchains.” <i>42nd International Conference on Distributed Computing Systems Workshops</i>, vol. 2022, IEEE, 2022, pp. 45–52, doi:<a href=\"https://doi.org/10.1109/icdcsw56584.2022.00018\">10.1109/icdcsw56584.2022.00018</a>."},"type":"conference","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","publication":"42nd International Conference on Distributed Computing Systems Workshops","day":"29","article_processing_charge":"No","year":"2022","date_created":"2023-01-12T12:09:28Z","external_id":{"isi":["000895984800009"]},"_id":"12160","date_published":"2022-11-29T00:00:00Z","doi":"10.1109/icdcsw56584.2022.00018","status":"public","date_updated":"2026-08-12T06:34:42Z","publication_identifier":{"eissn":["2332-5666"],"eisbn":["9781665488792"]},"quality_controlled":"1","title":"Hierarchical consensus: A horizontal scaling framework for blockchains","abstract":[{"text":"We present the Filecoin Hierarchical Consensus framework, which aims to overcome the throughput challenges of blockchain consensus by horizontally scaling the network. Unlike traditional sharding designs, based on partitioning the state of the network, our solution centers on the concept of subnets -which are organized hierarchically- and can be spawned on-demand to manage new state. Child sub nets are firewalled from parent subnets, have their own specific policies, and run a different consensus algorithm, increasing the network capacity and enabling new applications. Moreover, they benefit from the security of parent subnets by periodically checkpointing state. In this paper, we introduce the overall system architecture, our detailed designs for cross-net transaction handling, and the open questions that we are still exploring.","lang":"eng"}],"publisher":"IEEE"},{"project":[{"call_identifier":"H2020","_id":"fc2ed2f7-9c52-11eb-aca3-c01059dda49c","grant_number":"101034413","name":"IST-BRIDGE: International postdoctoral program"}],"doi":"10.1109/FOCS54457.2022.00091","date_updated":"2026-08-12T06:34:24Z","status":"public","publisher":"IEEE","abstract":[{"lang":"eng","text":"We present CertifyHAM, a deterministic algorithm that takes a graph G as input and either finds a Hamilton cycle of G or outputs that such a cycle does not exist. If G ∼ G(n, p) and p ≥\r\n100 log n/n then the expected running time of CertifyHAM is O(n/p) which is best possible. This improves upon previous results due to Gurevich and Shelah, Thomason and Alon, and\r\nKrivelevich, who proved analogous results for p being constant, p ≥ 12n −1/3 and p ≥ 70n\r\n−1/2 respectively."}],"title":"Solving the Hamilton cycle problem fast on average","quality_controlled":"1","publication_identifier":{"isbn":["9781665455190"],"issn":["0272-5428"]},"article_processing_charge":"No","day":"01","type":"conference","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","publication":"63rd Annual IEEE Symposium on Foundations of Computer Science","date_created":"2023-01-29T23:00:59Z","date_published":"2022-12-01T00:00:00Z","_id":"12432","external_id":{"isi":["000909382900084"]},"year":"2022","ec_funded":1,"corr_author":"1","citation":{"ista":"Anastos M. 2022. Solving the Hamilton cycle problem fast on average. 63rd Annual IEEE Symposium on Foundations of Computer Science. FOCS: Foundations of Computer Science vol. 2022–October, 919–930.","chicago":"Anastos, Michael. “Solving the Hamilton Cycle Problem Fast on Average.” In <i>63rd Annual IEEE Symposium on Foundations of Computer Science</i>, 2022–October:919–30. IEEE, 2022. <a href=\"https://doi.org/10.1109/FOCS54457.2022.00091\">https://doi.org/10.1109/FOCS54457.2022.00091</a>.","ieee":"M. Anastos, “Solving the Hamilton cycle problem fast on average,” in <i>63rd Annual IEEE Symposium on Foundations of Computer Science</i>, Denver, CO, United States, 2022, vol. 2022–October, pp. 919–930.","mla":"Anastos, Michael. “Solving the Hamilton Cycle Problem Fast on Average.” <i>63rd Annual IEEE Symposium on Foundations of Computer Science</i>, vol. 2022–October, IEEE, 2022, pp. 919–30, doi:<a href=\"https://doi.org/10.1109/FOCS54457.2022.00091\">10.1109/FOCS54457.2022.00091</a>.","short":"M. Anastos, in:, 63rd Annual IEEE Symposium on Foundations of Computer Science, IEEE, 2022, pp. 919–930.","ama":"Anastos M. Solving the Hamilton cycle problem fast on average. In: <i>63rd Annual IEEE Symposium on Foundations of Computer Science</i>. Vol 2022-October. IEEE; 2022:919-930. doi:<a href=\"https://doi.org/10.1109/FOCS54457.2022.00091\">10.1109/FOCS54457.2022.00091</a>","apa":"Anastos, M. (2022). Solving the Hamilton cycle problem fast on average. In <i>63rd Annual IEEE Symposium on Foundations of Computer Science</i> (Vol. 2022–October, pp. 919–930). Denver, CO, United States: IEEE. <a href=\"https://doi.org/10.1109/FOCS54457.2022.00091\">https://doi.org/10.1109/FOCS54457.2022.00091</a>"},"scopus_import":"1","acknowledgement":"This project has received funding from the European Union’s Horizon 2020\r\nresearch and innovation programme under the Marie Skłodowska-Curie grant\r\nagreement No 101034413","isi":1,"publication_status":"published","department":[{"_id":"MaKw"}],"conference":{"end_date":"2022-11-03","location":"Denver, CO, United States","start_date":"2022-10-31","name":"FOCS: Foundations of Computer Science"},"author":[{"last_name":"Anastos","full_name":"Anastos, Michael","id":"0b2a4358-bb35-11ec-b7b9-e3279b593dbb","first_name":"Michael"}],"month":"12","volume":"2022-October","language":[{"iso":"eng"}],"page":"919-930","oa_version":"None"},{"citation":{"mla":"Yadav, Anuj Kumar, et al. “New Results on AVCs with Omniscient and Myopic Adversaries.” <i>2022 IEEE International Symposium on Information Theory</i>, vol. 2022, IEEE, 2022, pp. 2535–40, doi:<a href=\"https://doi.org/10.1109/ISIT50566.2022.9834632\">10.1109/ISIT50566.2022.9834632</a>.","ieee":"A. K. Yadav, M. Alimohammadi, Y. Zhang, A. J. Budkuley, and S. Jaggi, “New results on AVCs with omniscient and myopic adversaries,” in <i>2022 IEEE International Symposium on Information Theory</i>, Espoo, Finland, 2022, vol. 2022, pp. 2535–2540.","chicago":"Yadav, Anuj Kumar, Mohammadreza Alimohammadi, Yihan Zhang, Amitalok J. Budkuley, and Sidharth Jaggi. “New Results on AVCs with Omniscient and Myopic Adversaries.” In <i>2022 IEEE International Symposium on Information Theory</i>, 2022:2535–40. IEEE, 2022. <a href=\"https://doi.org/10.1109/ISIT50566.2022.9834632\">https://doi.org/10.1109/ISIT50566.2022.9834632</a>.","ista":"Yadav AK, Alimohammadi M, Zhang Y, Budkuley AJ, Jaggi S. 2022. New results on AVCs with omniscient and myopic adversaries. 2022 IEEE International Symposium on Information Theory. ISIT: Internation Symposium on Information Theory vol. 2022, 2535–2540.","apa":"Yadav, A. K., Alimohammadi, M., Zhang, Y., Budkuley, A. J., &#38; Jaggi, S. (2022). New results on AVCs with omniscient and myopic adversaries. In <i>2022 IEEE International Symposium on Information Theory</i> (Vol. 2022, pp. 2535–2540). Espoo, Finland: IEEE. <a href=\"https://doi.org/10.1109/ISIT50566.2022.9834632\">https://doi.org/10.1109/ISIT50566.2022.9834632</a>","ama":"Yadav AK, Alimohammadi M, Zhang Y, Budkuley AJ, Jaggi S. New results on AVCs with omniscient and myopic adversaries. In: <i>2022 IEEE International Symposium on Information Theory</i>. Vol 2022. IEEE; 2022:2535-2540. doi:<a href=\"https://doi.org/10.1109/ISIT50566.2022.9834632\">10.1109/ISIT50566.2022.9834632</a>","short":"A.K. Yadav, M. Alimohammadi, Y. Zhang, A.J. Budkuley, S. Jaggi, in:, 2022 IEEE International Symposium on Information Theory, IEEE, 2022, pp. 2535–2540."},"scopus_import":"1","intvolume":"      2022","author":[{"first_name":"Anuj Kumar","full_name":"Yadav, Anuj Kumar","last_name":"Yadav"},{"first_name":"Mohammadreza","full_name":"Alimohammadi, Mohammadreza","last_name":"Alimohammadi"},{"full_name":"Zhang, Yihan","last_name":"Zhang","orcid":"0000-0002-6465-6258","id":"2ce5da42-b2ea-11eb-bba5-9f264e9d002c","first_name":"Yihan"},{"full_name":"Budkuley, Amitalok J.","last_name":"Budkuley","first_name":"Amitalok J."},{"first_name":"Sidharth","last_name":"Jaggi","full_name":"Jaggi, Sidharth"}],"department":[{"_id":"MaMo"}],"conference":{"end_date":"2022-07-01","location":"Espoo, Finland","start_date":"2022-06-26","name":"ISIT: Internation Symposium on Information Theory"},"isi":1,"publication_status":"published","month":"08","volume":2022,"language":[{"iso":"eng"}],"oa_version":"None","page":"2535-2540","date_updated":"2026-08-12T06:36:54Z","status":"public","doi":"10.1109/ISIT50566.2022.9834632","quality_controlled":"1","title":"New results on AVCs with omniscient and myopic adversaries","abstract":[{"lang":"eng","text":"In the classic adversarial communication problem, two parties communicate over a noisy channel in the presence of a malicious jamming adversary. The arbitrarily varying channels (AVCs) offer an elegant framework to study a wide range of interesting adversary models. The optimal throughput or capacity over such AVCs is intimately tied to the underlying adversary model; in some cases, capacity is unknown and the problem is known to be notoriously hard. The omniscient adversary, one which knows the sender’s entire channel transmission a priori, is one of such classic models of interest; the capacity under such an adversary remains an exciting open problem. The myopic adversary is a generalization of that model where the adversary’s observation may be corrupted over a noisy discrete memoryless channel. Through the adversary’s myopicity, one can unify the slew of different adversary models, ranging from the omniscient adversary to one that is completely blind to the transmission (the latter is the well known oblivious model where the capacity is fully characterized).In this work, we present new results on the capacity under both the omniscient and myopic adversary models. We completely characterize the positive capacity threshold over general AVCs with omniscient adversaries. The characterization is in terms of two key combinatorial objects: the set of completely positive distributions and the CP-confusability set. For omniscient AVCs with positive capacity, we present non-trivial lower and upper bounds on the capacity; unlike some of the previous bounds, our bounds hold under fairly general input and jamming constraints. Our lower bound improves upon the generalized Gilbert-Varshamov bound for general AVCs while the upper bound generalizes the well known Elias-Bassalygo bound (known for binary and q-ary alphabets). For the myopic AVCs, we build on prior results known for the so-called sufficiently myopic model, and present new results on the positive rate communication threshold over the so-called insufficiently myopic regime (a completely insufficient myopic adversary specializes to an omniscient adversary). We present interesting examples for the widely studied models of adversarial bit-flip and bit-erasure channels. In fact, for the bit-flip AVC with additive adversarial noise as well as random noise, we completely characterize the omniscient model capacity when the random noise is sufficiently large vis-a-vis the adversary’s budget."}],"publisher":"IEEE","publication_identifier":{"issn":["2157-8095"],"isbn":["9781665421591"]},"day":"03","article_processing_charge":"No","type":"conference","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","publication":"2022 IEEE International Symposium on Information Theory","date_created":"2022-09-04T22:02:06Z","_id":"12017","external_id":{"isi":["001254261902116"]},"date_published":"2022-08-03T00:00:00Z","year":"2022"},{"year":"2022","_id":"12018","external_id":{"isi":["001254261901080"]},"date_published":"2022-08-03T00:00:00Z","date_created":"2022-09-04T22:02:06Z","publication":"2022 IEEE International Symposium on Information Theory","type":"conference","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","day":"03","article_processing_charge":"No","publication_identifier":{"isbn":["9781665421591"],"issn":["2157-8095"]},"abstract":[{"text":"We study the problem of characterizing the maximal rates of list decoding in Euclidean spaces for finite list sizes. For any positive integer L ≥ 2 and real N > 0, we say that a subset C⊂Rn is an (N,L – 1)-multiple packing or an (N,L– 1)-list decodable code if every Euclidean ball of radius nN−−−√ in ℝ n contains no more than L − 1 points of C. We study this problem with and without ℓ 2 norm constraints on C, and derive the best-known lower bounds on the maximal rate for (N,L−1) multiple packing. Our bounds are obtained via error exponents for list decoding over Additive White Gaussian Noise (AWGN) channels. We establish a curious inequality which relates the error exponent, a quantity of average-case nature, to the list-decoding radius, a quantity of worst-case nature. We derive various bounds on the error exponent for list decoding in both bounded and unbounded settings which could be of independent interest beyond multiple packing.","lang":"eng"}],"quality_controlled":"1","title":"Lower bounds on list decoding capacity using error exponents","publisher":"IEEE","status":"public","date_updated":"2026-08-12T06:37:09Z","doi":"10.1109/ISIT50566.2022.9834815","oa_version":"None","page":"1324-1329","language":[{"iso":"eng"}],"volume":2022,"month":"08","department":[{"_id":"MaMo"}],"conference":{"location":"Espoo, Finland","start_date":"2022-06-26","end_date":"2022-07-01","name":"ISIT: International Symposium on Information Theory"},"author":[{"orcid":"0000-0002-6465-6258","full_name":"Zhang, Yihan","last_name":"Zhang","id":"2ce5da42-b2ea-11eb-bba5-9f264e9d002c","first_name":"Yihan"},{"first_name":"Shashank","full_name":"Vatedka, Shashank","last_name":"Vatedka"}],"isi":1,"publication_status":"published","scopus_import":"1","intvolume":"      2022","citation":{"ista":"Zhang Y, Vatedka S. 2022. Lower bounds on list decoding capacity using error exponents. 2022 IEEE International Symposium on Information Theory. ISIT: International Symposium on Information Theory vol. 2022, 1324–1329.","chicago":"Zhang, Yihan, and Shashank Vatedka. “Lower Bounds on List Decoding Capacity Using Error Exponents.” In <i>2022 IEEE International Symposium on Information Theory</i>, 2022:1324–29. IEEE, 2022. <a href=\"https://doi.org/10.1109/ISIT50566.2022.9834815\">https://doi.org/10.1109/ISIT50566.2022.9834815</a>.","ieee":"Y. Zhang and S. Vatedka, “Lower bounds on list decoding capacity using error exponents,” in <i>2022 IEEE International Symposium on Information Theory</i>, Espoo, Finland, 2022, vol. 2022, pp. 1324–1329.","mla":"Zhang, Yihan, and Shashank Vatedka. “Lower Bounds on List Decoding Capacity Using Error Exponents.” <i>2022 IEEE International Symposium on Information Theory</i>, vol. 2022, IEEE, 2022, pp. 1324–29, doi:<a href=\"https://doi.org/10.1109/ISIT50566.2022.9834815\">10.1109/ISIT50566.2022.9834815</a>.","short":"Y. Zhang, S. Vatedka, in:, 2022 IEEE International Symposium on Information Theory, IEEE, 2022, pp. 1324–1329.","ama":"Zhang Y, Vatedka S. Lower bounds on list decoding capacity using error exponents. In: <i>2022 IEEE International Symposium on Information Theory</i>. Vol 2022. IEEE; 2022:1324-1329. doi:<a href=\"https://doi.org/10.1109/ISIT50566.2022.9834815\">10.1109/ISIT50566.2022.9834815</a>","apa":"Zhang, Y., &#38; Vatedka, S. (2022). Lower bounds on list decoding capacity using error exponents. In <i>2022 IEEE International Symposium on Information Theory</i> (Vol. 2022, pp. 1324–1329). Espoo, Finland: IEEE. <a href=\"https://doi.org/10.1109/ISIT50566.2022.9834815\">https://doi.org/10.1109/ISIT50566.2022.9834815</a>"}},{"publication_identifier":{"issn":["2157-8095"],"isbn":["9781665421591"]},"publisher":"IEEE","quality_controlled":"1","abstract":[{"lang":"eng","text":"This paper studies combinatorial properties of codes for the Z-channel. A Z-channel with error fraction τ takes as input a length-n binary codeword and injects in an adversarial manner up to nτ asymmetric errors, i.e., errors that only zero out bits but do not flip 0’s to 1’s. It is known that the largest (L − 1)-list-decodable code for the Z-channel with error fraction τ has exponential (in n) size if τ is less than a critical value that we call the Plotkin point and has constant size if τ is larger than the threshold. The (L−1)-list-decoding Plotkin point is known to be L−1L−1−L−LL−1. In this paper, we show that the largest (L−1)-list-decodable code ε-above the Plotkin point has size Θ L (ε −3/2 ) for any L − 1 ≥ 1."}],"title":"List-decodable zero-rate codes for the Z-channel","date_updated":"2026-08-12T06:37:29Z","status":"public","doi":"10.1109/ISIT50566.2022.9834829","year":"2022","date_created":"2022-09-04T22:02:07Z","date_published":"2022-08-03T00:00:00Z","external_id":{"isi":["001254261902119"]},"_id":"12019","type":"conference","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","publication":"2022 IEEE International Symposium on Information Theory","article_processing_charge":"No","day":"03","citation":{"short":"N. Polyanskii, Y. Zhang, in:, 2022 IEEE International Symposium on Information Theory, IEEE, 2022, pp. 2553–2558.","ama":"Polyanskii N, Zhang Y. List-decodable zero-rate codes for the Z-channel. In: <i>2022 IEEE International Symposium on Information Theory</i>. Vol 2022. IEEE; 2022:2553-2558. doi:<a href=\"https://doi.org/10.1109/ISIT50566.2022.9834829\">10.1109/ISIT50566.2022.9834829</a>","apa":"Polyanskii, N., &#38; Zhang, Y. (2022). List-decodable zero-rate codes for the Z-channel. In <i>2022 IEEE International Symposium on Information Theory</i> (Vol. 2022, pp. 2553–2558). Espoo, Finland: IEEE. <a href=\"https://doi.org/10.1109/ISIT50566.2022.9834829\">https://doi.org/10.1109/ISIT50566.2022.9834829</a>","ista":"Polyanskii N, Zhang Y. 2022. List-decodable zero-rate codes for the Z-channel. 2022 IEEE International Symposium on Information Theory. ISIT: International Symposium on Information Theory vol. 2022, 2553–2558.","chicago":"Polyanskii, Nikita, and Yihan Zhang. “List-Decodable Zero-Rate Codes for the Z-Channel.” In <i>2022 IEEE International Symposium on Information Theory</i>, 2022:2553–58. IEEE, 2022. <a href=\"https://doi.org/10.1109/ISIT50566.2022.9834829\">https://doi.org/10.1109/ISIT50566.2022.9834829</a>.","ieee":"N. Polyanskii and Y. Zhang, “List-decodable zero-rate codes for the Z-channel,” in <i>2022 IEEE International Symposium on Information Theory</i>, Espoo, Finland, 2022, vol. 2022, pp. 2553–2558.","mla":"Polyanskii, Nikita, and Yihan Zhang. “List-Decodable Zero-Rate Codes for the Z-Channel.” <i>2022 IEEE International Symposium on Information Theory</i>, vol. 2022, IEEE, 2022, pp. 2553–58, doi:<a href=\"https://doi.org/10.1109/ISIT50566.2022.9834829\">10.1109/ISIT50566.2022.9834829</a>."},"language":[{"iso":"eng"}],"page":"2553-2558","oa_version":"None","isi":1,"publication_status":"published","conference":{"end_date":"2022-07-01","location":"Espoo, Finland","start_date":"2022-06-26","name":"ISIT: International Symposium on Information Theory"},"department":[{"_id":"MaMo"}],"author":[{"full_name":"Polyanskii, Nikita","last_name":"Polyanskii","first_name":"Nikita"},{"orcid":"0000-0002-6465-6258","full_name":"Zhang, Yihan","last_name":"Zhang","id":"2ce5da42-b2ea-11eb-bba5-9f264e9d002c","first_name":"Yihan"}],"volume":2022,"month":"08","intvolume":"      2022","scopus_import":"1"},{"corr_author":"1","article_number":"2204.07373","citation":{"short":"M. Lechner, A. Amini, D. Rus, T.A. Henzinger, ArXiv (n.d.).","ama":"Lechner M, Amini A, Rus D, Henzinger TA. Revisiting the adversarial robustness-accuracy tradeoff in robot learning. <i>arXiv</i>. doi:<a href=\"https://doi.org/10.48550/arXiv.2204.07373\">10.48550/arXiv.2204.07373</a>","apa":"Lechner, M., Amini, A., Rus, D., &#38; Henzinger, T. A. (n.d.). Revisiting the adversarial robustness-accuracy tradeoff in robot learning. <i>arXiv</i>. <a href=\"https://doi.org/10.48550/arXiv.2204.07373\">https://doi.org/10.48550/arXiv.2204.07373</a>","ista":"Lechner M, Amini A, Rus D, Henzinger TA. Revisiting the adversarial robustness-accuracy tradeoff in robot learning. arXiv, 2204.07373.","ieee":"M. Lechner, A. Amini, D. Rus, and T. A. Henzinger, “Revisiting the adversarial robustness-accuracy tradeoff in robot learning,” <i>arXiv</i>. .","chicago":"Lechner, Mathias, Alexander Amini, Daniela Rus, and Thomas A Henzinger. “Revisiting the Adversarial Robustness-Accuracy Tradeoff in Robot Learning.” <i>ArXiv</i>, n.d. <a href=\"https://doi.org/10.48550/arXiv.2204.07373\">https://doi.org/10.48550/arXiv.2204.07373</a>.","mla":"Lechner, Mathias, et al. “Revisiting the Adversarial Robustness-Accuracy Tradeoff in Robot Learning.” <i>ArXiv</i>, 2204.07373, doi:<a href=\"https://doi.org/10.48550/arXiv.2204.07373\">10.48550/arXiv.2204.07373</a>."},"ec_funded":1,"related_material":{"record":[{"relation":"dissertation_contains","status":"public","id":"11362"},{"relation":"later_version","id":"12704","status":"public"}]},"OA_place":"repository","oa_version":"Preprint","language":[{"iso":"eng"}],"month":"04","publication_status":"draft","author":[{"id":"3DC22916-F248-11E8-B48F-1D18A9856A87","first_name":"Mathias","full_name":"Lechner, Mathias","last_name":"Lechner"},{"first_name":"Alexander","full_name":"Amini, Alexander","last_name":"Amini"},{"first_name":"Daniela","last_name":"Rus","full_name":"Rus, Daniela"},{"id":"40876CD8-F248-11E8-B48F-1D18A9856A87","first_name":"Thomas A","last_name":"Henzinger","full_name":"Henzinger, Thomas A","orcid":"0000-0002-2985-7724"}],"department":[{"_id":"ToHe"}],"acknowledgement":"This work was supported in parts by the ERC-2020-AdG 101020093, National Science Foundation (NSF), and JP\r\nMorgan Graduate Fellowships. We thank Christoph Lampert for inspiring this work.\r\n","main_file_link":[{"url":"https://doi.org/10.48550/arXiv.2204.07373","open_access":"1"}],"title":"Revisiting the adversarial robustness-accuracy tradeoff in robot learning","abstract":[{"lang":"eng","text":"Adversarial training (i.e., training on adversarially perturbed input data) is a well-studied method for making neural networks robust to potential adversarial attacks during inference. However, the improved robustness does not\r\ncome for free but rather is accompanied by a decrease in overall model accuracy and performance. Recent work has shown that, in practical robot learning applications, the effects of adversarial training do not pose a fair trade-off\r\nbut inflict a net loss when measured in holistic robot performance. This work revisits the robustness-accuracy trade-off in robot learning by systematically analyzing if recent advances in robust training methods and theory in\r\nconjunction with adversarial robot learning can make adversarial training suitable for real-world robot applications. We evaluate a wide variety of robot learning tasks ranging from autonomous driving in a high-fidelity environment\r\namenable to sim-to-real deployment, to mobile robot gesture recognition. Our results demonstrate that, while these techniques make incremental improvements on the trade-off on a relative scale, the negative side-effects caused by\r\nadversarial training still outweigh the improvements by an order of magnitude. We conclude that more substantial advances in robust learning methods are necessary before they can benefit robot learning tasks in practice."}],"oa":1,"project":[{"call_identifier":"H2020","_id":"62781420-2b32-11ec-9570-8d9b63373d4d","name":"Vigilant Algorithmic Monitoring of Software","grant_number":"101020093"}],"date_updated":"2026-08-12T06:40:15Z","doi":"10.48550/arXiv.2204.07373","status":"public","arxiv":1,"year":"2022","date_published":"2022-04-15T00:00:00Z","_id":"11366","external_id":{"arxiv":["2204.07373"]},"date_created":"2022-05-12T13:20:17Z","publication":"arXiv","type":"preprint","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","article_processing_charge":"No","day":"15"},{"acknowledgement":"The authors would like to thank Amit Agarwal, Adithya Bhat, Kobi Gurkan, Dakshita Khurana, Nibesh Shrestha, and Gilad Stern for the helpful discussions related to the paper.\r\nAlso, the authors would like to thank Sylvain Bellemare for helping with the hbACSS codebase and Nicolas Gailly for helping with running the Drand experiments.","day":"27","scopus_import":"1","article_processing_charge":"No","month":"07","publication":"2022 IEEE Symposium on Security and Privacy","conference":{"end_date":"2022-05-26","location":"San Francisco, CA, United States","start_date":"2022-05-23","name":"SP: Symposium on Security and Privacy"},"author":[{"full_name":"Das, Sourav","last_name":"Das","first_name":"Sourav"},{"first_name":"Thomas","full_name":"Yurek, Thomas","last_name":"Yurek"},{"first_name":"Zhuolun","last_name":"Xiang","full_name":"Xiang, Zhuolun"},{"last_name":"Miller","full_name":"Miller, Andrew","first_name":"Andrew"},{"last_name":"Kokoris Kogias","full_name":"Kokoris Kogias, Eleftherios","orcid":"0000-0002-8827-3382","id":"f5983044-d7ef-11ea-ac6d-fd1430a26d30","first_name":"Eleftherios"},{"full_name":"Ren, Ling","last_name":"Ren","first_name":"Ling"}],"department":[{"_id":"ElKo"}],"publication_status":"published","type":"conference","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","_id":"12300","date_published":"2022-07-27T00:00:00Z","date_created":"2023-01-16T10:06:11Z","oa_version":"Preprint","page":"2518-2534","language":[{"iso":"eng"}],"year":"2022","date_updated":"2026-08-12T06:40:50Z","status":"public","doi":"10.1109/sp46214.2022.9833584","oa":1,"abstract":[{"lang":"eng","text":"Distributed Key Generation (DKG) is a technique to bootstrap threshold cryptosystems without a trusted third party and is a building block to decentralized protocols such as randomness beacons, threshold signatures, and general multiparty computation. Until recently, DKG protocols have assumed the synchronous model and thus are vulnerable when their underlying network assumptions do not hold. The recent advancements in asynchronous DKG protocols are insufficient as they either have poor efficiency or limited functionality, resulting in a lack of concrete implementations. In this paper, we present a simple and concretely efficient asynchronous DKG (ADKG) protocol. In a network of n nodes, our ADKG protocol can tolerate up to t<n/3 malicious nodes and have an expected O(κn3) communication cost, where κ is the security parameter. Our ADKG protocol produces a field element as the secret and is thus compatible with off-the-shelf threshold cryptosystems. We implement our ADKG protocol and evaluate it using a network of up to 128 nodes in geographically distributed AWS instances. Our evaluation shows that our protocol takes as low as 3 and 9.5 seconds to terminate for 32 and 64 nodes, respectively. Also, each node sends only 0.7 Megabytes and 2.9 Megabytes of data during the two experiments, respectively."}],"title":"Practical asynchronous distributed key generation","quality_controlled":"1","publisher":"IEEE","main_file_link":[{"url":"https://eprint.iacr.org/2021/1591","open_access":"1"}],"publication_identifier":{"eisbn":["9781665413169"],"eissn":["2375-1207"]},"citation":{"ista":"Das S, Yurek T, Xiang Z, Miller A, Kokoris Kogias E, Ren L. 2022. Practical asynchronous distributed key generation. 2022 IEEE Symposium on Security and Privacy. SP: Symposium on Security and Privacy, 2518–2534.","mla":"Das, Sourav, et al. “Practical Asynchronous Distributed Key Generation.” <i>2022 IEEE Symposium on Security and Privacy</i>, IEEE, 2022, pp. 2518–34, doi:<a href=\"https://doi.org/10.1109/sp46214.2022.9833584\">10.1109/sp46214.2022.9833584</a>.","chicago":"Das, Sourav, Thomas Yurek, Zhuolun Xiang, Andrew Miller, Eleftherios Kokoris Kogias, and Ling Ren. “Practical Asynchronous Distributed Key Generation.” In <i>2022 IEEE Symposium on Security and Privacy</i>, 2518–34. IEEE, 2022. <a href=\"https://doi.org/10.1109/sp46214.2022.9833584\">https://doi.org/10.1109/sp46214.2022.9833584</a>.","ieee":"S. Das, T. Yurek, Z. Xiang, A. Miller, E. Kokoris Kogias, and L. Ren, “Practical asynchronous distributed key generation,” in <i>2022 IEEE Symposium on Security and Privacy</i>, San Francisco, CA, United States, 2022, pp. 2518–2534.","short":"S. Das, T. Yurek, Z. Xiang, A. Miller, E. Kokoris Kogias, L. Ren, in:, 2022 IEEE Symposium on Security and Privacy, IEEE, 2022, pp. 2518–2534.","apa":"Das, S., Yurek, T., Xiang, Z., Miller, A., Kokoris Kogias, E., &#38; Ren, L. (2022). Practical asynchronous distributed key generation. In <i>2022 IEEE Symposium on Security and Privacy</i> (pp. 2518–2534). San Francisco, CA, United States: IEEE. <a href=\"https://doi.org/10.1109/sp46214.2022.9833584\">https://doi.org/10.1109/sp46214.2022.9833584</a>","ama":"Das S, Yurek T, Xiang Z, Miller A, Kokoris Kogias E, Ren L. Practical asynchronous distributed key generation. In: <i>2022 IEEE Symposium on Security and Privacy</i>. IEEE; 2022:2518-2534. doi:<a href=\"https://doi.org/10.1109/sp46214.2022.9833584\">10.1109/sp46214.2022.9833584</a>"}},{"year":"2022","date_created":"2023-01-16T10:01:19Z","_id":"12273","external_id":{"arxiv":["1801.05951"],"isi":["000838527100004"]},"date_published":"2022-08-01T00:00:00Z","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","type":"journal_article","publication":"IEEE Transactions on Information Theory","day":"01","article_processing_charge":"No","publication_identifier":{"issn":["0018-9448"],"eissn":["1557-9654"]},"main_file_link":[{"url":"https://doi.org/10.48550/arXiv.1801.05951","open_access":"1"}],"quality_controlled":"1","abstract":[{"text":"We study communication in the presence of a jamming adversary where quadratic power constraints are imposed on the transmitter and the jammer. The jamming signal is allowed to be a function of the codebook, and a noncausal but noisy observation of the transmitted codeword. For a certain range of the noise-to-signal ratios (NSRs) of the transmitter and the jammer, we are able to characterize the capacity of this channel under deterministic encoding or stochastic encoding, i.e., with no common randomness between the encoder/decoder pair. For the remaining NSR regimes, we determine the capacity under the assumption of a small amount of common randomness (at most 2log(n) bits in one sub-regime, and at most Ω(n) bits in the other sub-regime) available to the encoder-decoder pair. Our proof techniques involve a novel myopic list-decoding result for achievability, and a Plotkin-type push attack for the converse in a subregion of the NSRs, both of which may be of independent interest. We also give bounds on the strong secrecy capacity of this channel assuming that the jammer is simultaneously eavesdropping.","lang":"eng"}],"title":"Quadratically constrained myopic adversarial channels","publisher":"IEEE","article_type":"original","oa":1,"arxiv":1,"date_updated":"2026-08-12T06:41:20Z","status":"public","doi":"10.1109/tit.2022.3167554","language":[{"iso":"eng"}],"oa_version":"Preprint","page":"4901-4948","author":[{"orcid":"0000-0002-6465-6258","last_name":"Zhang","full_name":"Zhang, Yihan","id":"2ce5da42-b2ea-11eb-bba5-9f264e9d002c","first_name":"Yihan"},{"first_name":"Shashank","full_name":"Vatedka, Shashank","last_name":"Vatedka"},{"first_name":"Sidharth","last_name":"Jaggi","full_name":"Jaggi, Sidharth"},{"full_name":"Sarwate, Anand D.","last_name":"Sarwate","first_name":"Anand D."}],"department":[{"_id":"MaMo"}],"publication_status":"published","isi":1,"volume":68,"month":"08","scopus_import":"1","intvolume":"        68","citation":{"ista":"Zhang Y, Vatedka S, Jaggi S, Sarwate AD. 2022. Quadratically constrained myopic adversarial channels. IEEE Transactions on Information Theory. 68(8), 4901–4948.","ieee":"Y. Zhang, S. Vatedka, S. Jaggi, and A. D. Sarwate, “Quadratically constrained myopic adversarial channels,” <i>IEEE Transactions on Information Theory</i>, vol. 68, no. 8. IEEE, pp. 4901–4948, 2022.","chicago":"Zhang, Yihan, Shashank Vatedka, Sidharth Jaggi, and Anand D. Sarwate. “Quadratically Constrained Myopic Adversarial Channels.” <i>IEEE Transactions on Information Theory</i>. IEEE, 2022. <a href=\"https://doi.org/10.1109/tit.2022.3167554\">https://doi.org/10.1109/tit.2022.3167554</a>.","mla":"Zhang, Yihan, et al. “Quadratically Constrained Myopic Adversarial Channels.” <i>IEEE Transactions on Information Theory</i>, vol. 68, no. 8, IEEE, 2022, pp. 4901–48, doi:<a href=\"https://doi.org/10.1109/tit.2022.3167554\">10.1109/tit.2022.3167554</a>.","short":"Y. Zhang, S. Vatedka, S. Jaggi, A.D. Sarwate, IEEE Transactions on Information Theory 68 (2022) 4901–4948.","ama":"Zhang Y, Vatedka S, Jaggi S, Sarwate AD. Quadratically constrained myopic adversarial channels. <i>IEEE Transactions on Information Theory</i>. 2022;68(8):4901-4948. doi:<a href=\"https://doi.org/10.1109/tit.2022.3167554\">10.1109/tit.2022.3167554</a>","apa":"Zhang, Y., Vatedka, S., Jaggi, S., &#38; Sarwate, A. D. (2022). Quadratically constrained myopic adversarial channels. <i>IEEE Transactions on Information Theory</i>. IEEE. <a href=\"https://doi.org/10.1109/tit.2022.3167554\">https://doi.org/10.1109/tit.2022.3167554</a>"},"corr_author":"1","issue":"8"},{"issue":"11","citation":{"ieee":"N. Doan, S. A. Hashemi, M. Mondelli, and W. J. Gross, “Decoding Reed-Muller codes with successive codeword permutations,” <i>IEEE Transactions on Communications</i>, vol. 70, no. 11. IEEE, pp. 7134–7145, 2022.","chicago":"Doan, Nghia, Seyyed Ali Hashemi, Marco Mondelli, and Warren J. Gross. “Decoding Reed-Muller Codes with Successive Codeword Permutations.” <i>IEEE Transactions on Communications</i>. IEEE, 2022. <a href=\"https://doi.org/10.1109/tcomm.2022.3211101\">https://doi.org/10.1109/tcomm.2022.3211101</a>.","mla":"Doan, Nghia, et al. “Decoding Reed-Muller Codes with Successive Codeword Permutations.” <i>IEEE Transactions on Communications</i>, vol. 70, no. 11, IEEE, 2022, pp. 7134–45, doi:<a href=\"https://doi.org/10.1109/tcomm.2022.3211101\">10.1109/tcomm.2022.3211101</a>.","ista":"Doan N, Hashemi SA, Mondelli M, Gross WJ. 2022. Decoding Reed-Muller codes with successive codeword permutations. IEEE Transactions on Communications. 70(11), 7134–7145.","ama":"Doan N, Hashemi SA, Mondelli M, Gross WJ. Decoding Reed-Muller codes with successive codeword permutations. <i>IEEE Transactions on Communications</i>. 2022;70(11):7134-7145. doi:<a href=\"https://doi.org/10.1109/tcomm.2022.3211101\">10.1109/tcomm.2022.3211101</a>","apa":"Doan, N., Hashemi, S. A., Mondelli, M., &#38; Gross, W. J. (2022). Decoding Reed-Muller codes with successive codeword permutations. <i>IEEE Transactions on Communications</i>. IEEE. <a href=\"https://doi.org/10.1109/tcomm.2022.3211101\">https://doi.org/10.1109/tcomm.2022.3211101</a>","short":"N. Doan, S.A. Hashemi, M. Mondelli, W.J. Gross, IEEE Transactions on Communications 70 (2022) 7134–7145."},"oa_version":"Preprint","page":"7134-7145","language":[{"iso":"eng"}],"month":"11","volume":70,"author":[{"last_name":"Doan","full_name":"Doan, Nghia","first_name":"Nghia"},{"full_name":"Hashemi, Seyyed Ali","last_name":"Hashemi","first_name":"Seyyed Ali"},{"first_name":"Marco","id":"27EB676C-8706-11E9-9510-7717E6697425","last_name":"Mondelli","full_name":"Mondelli, Marco","orcid":"0000-0002-3242-7020"},{"full_name":"Gross, Warren J.","last_name":"Gross","first_name":"Warren J."}],"department":[{"_id":"MaMo"}],"publication_status":"published","isi":1,"scopus_import":"1","intvolume":"        70","main_file_link":[{"url":" https://doi.org/10.48550/arXiv.2109.02122","open_access":"1"}],"publication_identifier":{"eissn":["1558-0857"],"issn":["0090-6778"]},"quality_controlled":"1","abstract":[{"text":"A novel recursive list decoding (RLD) algorithm for Reed-Muller (RM) codes based on successive permutations (SP) of the codeword is presented. A low-complexity SP scheme applied to a subset of the symmetry group of RM codes is first proposed to carefully select a good codeword permutation on the fly. Then, the proposed SP technique is integrated into an improved RLD algorithm that initializes different decoding paths with random codeword permutations, which are sampled from the full symmetry group of RM codes. Finally, efficient latency and complexity reduction schemes are introduced that virtually preserve the error-correction performance of the proposed decoder. Simulation results demonstrate that at the target frame error rate of 10−3 for the RM code of length 256 with 163 information bits, the proposed decoder reduces 6% of the computational complexity and 22% of the decoding latency of the state-of-the-art semi-parallel simplified successive-cancellation decoder with fast Hadamard transform (SSC-FHT) that uses 96 permutations from the full symmetry group of RM codes, while relatively maintaining the error-correction performance and memory consumption of the semi-parallel permuted SSC-FHT decoder.","lang":"eng"}],"title":"Decoding Reed-Muller codes with successive codeword permutations","publisher":"IEEE","oa":1,"article_type":"original","status":"public","date_updated":"2026-08-12T06:41:04Z","doi":"10.1109/tcomm.2022.3211101","arxiv":1,"year":"2022","external_id":{"arxiv":["2109.02122"],"isi":["000937284600006"]},"_id":"12233","date_published":"2022-11-01T00:00:00Z","date_created":"2023-01-16T09:50:38Z","publication":"IEEE Transactions on Communications","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","type":"journal_article","day":"01","article_processing_charge":"No"},{"language":[{"iso":"eng"}],"oa_version":"Preprint","page":"3909-3920","scopus_import":"1","intvolume":"        21","acknowledgement":"S. A. Hashemi is supported by a Postdoctoral Fellowship from the Natural Sciences and\r\nEngineering Research Council of Canada (NSERC) and by Huawei. M. Mondelli is partially\r\nsupported by the 2019 Lopez-Loreta Prize. A. Fazeli and A. Vardy were supported in part by\r\nthe National Science Foundation under Grant CCF-1764104.","author":[{"first_name":"Seyyed Ali","last_name":"Hashemi","full_name":"Hashemi, Seyyed Ali"},{"last_name":"Mondelli","full_name":"Mondelli, Marco","orcid":"0000-0002-3242-7020","first_name":"Marco","id":"27EB676C-8706-11E9-9510-7717E6697425"},{"first_name":"Arman","full_name":"Fazeli, Arman","last_name":"Fazeli"},{"first_name":"Alexander","full_name":"Vardy, Alexander","last_name":"Vardy"},{"first_name":"John","last_name":"Cioffi","full_name":"Cioffi, John"},{"first_name":"Andrea","full_name":"Goldsmith, Andrea","last_name":"Goldsmith"}],"department":[{"_id":"MaMo"}],"publication_status":"published","isi":1,"volume":21,"month":"06","related_material":{"record":[{"status":"public","id":"10053","relation":"earlier_version"}]},"citation":{"ista":"Hashemi SA, Mondelli M, Fazeli A, Vardy A, Cioffi J, Goldsmith A. 2022. Parallelism versus latency in simplified successive-cancellation decoding of polar codes. IEEE Transactions on Wireless Communications. 21(6), 3909–3920.","ieee":"S. A. Hashemi, M. Mondelli, A. Fazeli, A. Vardy, J. Cioffi, and A. Goldsmith, “Parallelism versus latency in simplified successive-cancellation decoding of polar codes,” <i>IEEE Transactions on Wireless Communications</i>, vol. 21, no. 6. IEEE, pp. 3909–3920, 2022.","chicago":"Hashemi, Seyyed Ali, Marco Mondelli, Arman Fazeli, Alexander Vardy, John Cioffi, and Andrea Goldsmith. “Parallelism versus Latency in Simplified Successive-Cancellation Decoding of Polar Codes.” <i>IEEE Transactions on Wireless Communications</i>. IEEE, 2022. <a href=\"https://doi.org/10.1109/TWC.2021.3125626\">https://doi.org/10.1109/TWC.2021.3125626</a>.","mla":"Hashemi, Seyyed Ali, et al. “Parallelism versus Latency in Simplified Successive-Cancellation Decoding of Polar Codes.” <i>IEEE Transactions on Wireless Communications</i>, vol. 21, no. 6, IEEE, 2022, pp. 3909–20, doi:<a href=\"https://doi.org/10.1109/TWC.2021.3125626\">10.1109/TWC.2021.3125626</a>.","short":"S.A. Hashemi, M. Mondelli, A. Fazeli, A. Vardy, J. Cioffi, A. Goldsmith, IEEE Transactions on Wireless Communications 21 (2022) 3909–3920.","ama":"Hashemi SA, Mondelli M, Fazeli A, Vardy A, Cioffi J, Goldsmith A. Parallelism versus latency in simplified successive-cancellation decoding of polar codes. <i>IEEE Transactions on Wireless Communications</i>. 2022;21(6):3909-3920. doi:<a href=\"https://doi.org/10.1109/TWC.2021.3125626\">10.1109/TWC.2021.3125626</a>","apa":"Hashemi, S. A., Mondelli, M., Fazeli, A., Vardy, A., Cioffi, J., &#38; Goldsmith, A. (2022). Parallelism versus latency in simplified successive-cancellation decoding of polar codes. <i>IEEE Transactions on Wireless Communications</i>. IEEE. <a href=\"https://doi.org/10.1109/TWC.2021.3125626\">https://doi.org/10.1109/TWC.2021.3125626</a>"},"issue":"6","date_created":"2021-11-28T23:01:29Z","external_id":{"arxiv":["2012.13378"],"isi":["000809406400028"]},"_id":"10364","date_published":"2022-06-01T00:00:00Z","year":"2022","day":"01","article_processing_charge":"No","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","type":"journal_article","publication":"IEEE Transactions on Wireless Communications","quality_controlled":"1","abstract":[{"text":"This paper characterizes the latency of the simplified successive-cancellation (SSC) decoding scheme for polar codes under hardware resource constraints. In particular, when the number of processing elements P that can perform SSC decoding operations in parallel is limited, as is the case in practice, the latency of SSC decoding is O(N1-1/μ + N/P log2 log2 N/P), where N is the block length of the code and μ is the scaling exponent of the channel. Three direct consequences of this bound are presented. First, in a fully-parallel implementation where P = N/2, the latency of SSC decoding is O(N1-1/μ), which is sublinear in the block length. This recovers a result from our earlier work. Second, in a fully-serial implementation where P = 1, the latency of SSC decoding scales as O(N log2 log2 N). The multiplicative constant is also calculated: we show that the latency of SSC decoding when P = 1 is given by (2 + o(1))N log2 log2 N. Third, in a semi-parallel implementation, the smallest P that gives the same latency as that of the fully-parallel implementation is P = N1/μ. The tightness of our bound on SSC decoding latency and the applicability of the foregoing results is validated through extensive simulations.","lang":"eng"}],"title":"Parallelism versus latency in simplified successive-cancellation decoding of polar codes","publisher":"IEEE","publication_identifier":{"issn":["1536-1276"],"eissn":["1558-2248"]},"main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/2012.13378"}],"arxiv":1,"date_updated":"2026-08-12T06:43:01Z","status":"public","doi":"10.1109/TWC.2021.3125626","project":[{"name":"Prix Lopez-Loretta 2019 - Marco Mondelli","_id":"059876FA-7A3F-11EA-A408-12923DDC885E"}],"article_type":"original","oa":1}]