[{"intvolume":"        39","_id":"14087","pmid":1,"publication_identifier":{"issn":["1744-683X"],"eissn":["1744-6848"]},"publication_status":"published","type":"journal_article","doi":"10.1039/d3sm00316g","isi":1,"article_type":"original","fulldoi":"https://doi.org/10.1039/d3sm00316g","file_date_updated":"2024-01-30T12:48:24Z","has_accepted_license":"1","quality_controlled":"1","article_processing_charge":"Yes (in subscription journal)","day":"01","date_created":"2023-08-20T22:01:15Z","author":[{"first_name":"Jonas","last_name":"Rønning","full_name":"Rønning, Jonas"},{"id":"7af6767d-14eb-11ed-b536-a32449ae867c","full_name":"Renaud, Julian B","last_name":"Renaud","first_name":"Julian B"},{"full_name":"Doostmohammadi, Amin","first_name":"Amin","last_name":"Doostmohammadi"},{"last_name":"Angheluta","first_name":"Luiza","full_name":"Angheluta, Luiza"}],"publisher":"Royal Society of Chemistry","citation":{"ama":"Rønning J, Renaud JB, Doostmohammadi A, Angheluta L. Spontaneous flows and dynamics of full-integer topological defects in polar active matter. <i>Soft Matter</i>. 2023;39:7513-7527. doi:<a href=\"https://doi.org/10.1039/d3sm00316g\">10.1039/d3sm00316g</a>","chicago":"Rønning, Jonas, Julian B Renaud, Amin Doostmohammadi, and Luiza Angheluta. “Spontaneous Flows and Dynamics of Full-Integer Topological Defects in Polar Active Matter.” <i>Soft Matter</i>. Royal Society of Chemistry, 2023. <a href=\"https://doi.org/10.1039/d3sm00316g\">https://doi.org/10.1039/d3sm00316g</a>.","short":"J. Rønning, J.B. Renaud, A. Doostmohammadi, L. Angheluta, Soft Matter 39 (2023) 7513–7527.","mla":"Rønning, Jonas, et al. “Spontaneous Flows and Dynamics of Full-Integer Topological Defects in Polar Active Matter.” <i>Soft Matter</i>, vol. 39, Royal Society of Chemistry, 2023, pp. 7513–27, doi:<a href=\"https://doi.org/10.1039/d3sm00316g\">10.1039/d3sm00316g</a>.","ista":"Rønning J, Renaud JB, Doostmohammadi A, Angheluta L. 2023. Spontaneous flows and dynamics of full-integer topological defects in polar active matter. Soft Matter. 39, 7513–7527.","ieee":"J. Rønning, J. B. Renaud, A. Doostmohammadi, and L. Angheluta, “Spontaneous flows and dynamics of full-integer topological defects in polar active matter,” <i>Soft Matter</i>, vol. 39. Royal Society of Chemistry, pp. 7513–7527, 2023.","apa":"Rønning, J., Renaud, J. B., Doostmohammadi, A., &#38; Angheluta, L. (2023). Spontaneous flows and dynamics of full-integer topological defects in polar active matter. <i>Soft Matter</i>. Royal Society of Chemistry. <a href=\"https://doi.org/10.1039/d3sm00316g\">https://doi.org/10.1039/d3sm00316g</a>"},"abstract":[{"lang":"eng","text":"Polar active matter of self-propelled particles sustain spontaneous flows through the full-integer topological defects. We study theoretically the incompressible flow profiles around ±1 defects induced by polar and dipolar active forces. We show that dipolar forces induce vortical flows around the +1 defect, while the flow around the −1 defect has an 8-fold rotational symmetry. The vortical flow changes its chirality near the +1 defect core in the absence of the friction with a substrate. We show analytically that the flow induced by polar active forces is vortical near the +1 defect and is 4-fold symmetric near the −1 defect, while it becomes uniform in the far-field. For a pair of oppositely charged defects, this polar flow contributes to a mutual interaction force that depends only on the orientation of the defect pair relative to the background polarization, and that enhances defect pair annihilation. This is in contradiction with the effect of dipolar active forces which decay inversely proportional with the defect separation distance. As such, our analyses reveals a long-ranged mechanism for the pairwise interaction between topological defects in polar active matter."}],"department":[{"_id":"GradSch"}],"language":[{"iso":"eng"}],"oa":1,"ddc":["540"],"oa_version":"Published Version","date_updated":"2025-04-23T13:03:12Z","volume":39,"status":"public","tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","image":"/images/cc_by.png","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)"},"title":"Spontaneous flows and dynamics of full-integer topological defects in polar active matter","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","scopus_import":"1","acknowledgement":"J. Rø and L. A. acknowledge support from the Research Council of Norway through the Center of Excellence funding scheme, Project No. 262644 (PoreLab). A. D. acknowledges funding from the Novo Nordisk Foundation (grant No. NNF18SA0035142 and NERD grant No. NNF21OC0068687), Villum Fonden Grant no. 29476, and the European Union via the ERC-Starting Grant PhysCoMeT. Views and opinions expressed are however those of the authors only and do not necessarily reflect those of the European Union or the European Research Council. Neither the European Union nor the granting authority can be held responsible for them.","arxiv":1,"month":"09","date_published":"2023-09-01T00:00:00Z","page":"7513-7527","external_id":{"arxiv":["2303.07063"],"pmid":["37493084"],"isi":["001035766100001"]},"file":[{"relation":"main_file","content_type":"application/pdf","file_name":"2023_SoftMatter_Ronning.pdf","creator":"dernst","file_id":"14908","file_size":7660662,"date_updated":"2024-01-30T12:48:24Z","checksum":"b936747170d0b708172b518078c4081a","access_level":"open_access","success":1,"date_created":"2024-01-30T12:48:24Z"}],"publication":"Soft Matter","year":"2023"},{"quality_controlled":"1","article_processing_charge":"No","article_type":"original","fulldoi":"https://doi.org/10.1051/0004-6361/202245650","publication_status":"published","type":"journal_article","doi":"10.1051/0004-6361/202245650","article_number":"A154","intvolume":"       675","_id":"14103","publication_identifier":{"eissn":["1432-0746"],"issn":["0004-6361"]},"external_id":{"arxiv":["2305.06376"]},"publication":"Astronomy & Astrophysics","extern":"1","year":"2023","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","keyword":["Space and Planetary Science","Astronomy and Astrophysics"],"scopus_import":"1","date_published":"2023-07-01T00:00:00Z","month":"07","arxiv":1,"oa_version":"Published Version","volume":675,"date_updated":"2023-08-22T11:01:07Z","title":"X-shooting ULLYSES: Massive stars at low metallicity. I. Project description","status":"public","day":"01","date_created":"2023-08-21T10:12:35Z","main_file_link":[{"open_access":"1","url":"https://doi.org/10.1051/0004-6361/202245650"}],"author":[{"full_name":"Vink, Jorick S.","first_name":"Jorick S.","last_name":"Vink"},{"full_name":"Mehner, A.","first_name":"A.","last_name":"Mehner"},{"first_name":"P. A.","last_name":"Crowther","full_name":"Crowther, P. A."},{"first_name":"A.","last_name":"Fullerton","full_name":"Fullerton, A."},{"last_name":"Garcia","first_name":"M.","full_name":"Garcia, M."},{"first_name":"F.","last_name":"Martins","full_name":"Martins, F."},{"first_name":"N.","last_name":"Morrell","full_name":"Morrell, N."},{"first_name":"L. M.","last_name":"Oskinova","full_name":"Oskinova, L. M."},{"full_name":"St-Louis, N.","last_name":"St-Louis","first_name":"N."},{"full_name":"ud-Doula, A.","last_name":"ud-Doula","first_name":"A."},{"full_name":"Sander, A. A. C.","first_name":"A. A. C.","last_name":"Sander"},{"last_name":"Sana","first_name":"H.","full_name":"Sana, H."},{"full_name":"Bouret, J.-C.","first_name":"J.-C.","last_name":"Bouret"},{"last_name":"Kubátová","first_name":"B.","full_name":"Kubátová, B."},{"full_name":"Marchant, P.","last_name":"Marchant","first_name":"P."},{"last_name":"Martins","first_name":"L. P.","full_name":"Martins, L. P."},{"last_name":"Wofford","first_name":"A.","full_name":"Wofford, A."},{"first_name":"J. Th.","last_name":"van Loon","full_name":"van Loon, J. Th."},{"full_name":"Grace Telford, O.","first_name":"O.","last_name":"Grace Telford"},{"full_name":"Götberg, Ylva Louise Linsdotter","orcid":"0000-0002-6960-6911","id":"d0648d0c-0f64-11ee-a2e0-dd0faa2e4f7d","first_name":"Ylva Louise Linsdotter","last_name":"Götberg"},{"full_name":"Bowman, D. M.","first_name":"D. M.","last_name":"Bowman"},{"full_name":"Erba, C.","first_name":"C.","last_name":"Erba"},{"last_name":"Kalari","first_name":"V. M.","full_name":"Kalari, V. M."},{"last_name":"Abdul-Masih","first_name":"M.","full_name":"Abdul-Masih, M."},{"last_name":"Alkousa","first_name":"T.","full_name":"Alkousa, T."},{"full_name":"Backs, F.","first_name":"F.","last_name":"Backs"},{"first_name":"C. L.","last_name":"Barbosa","full_name":"Barbosa, C. L."},{"full_name":"Berlanas, S. R.","last_name":"Berlanas","first_name":"S. R."},{"full_name":"Bernini-Peron, M.","last_name":"Bernini-Peron","first_name":"M."},{"full_name":"Bestenlehner, J. M.","last_name":"Bestenlehner","first_name":"J. M."},{"full_name":"Blomme, R.","last_name":"Blomme","first_name":"R."},{"full_name":"Bodensteiner, J.","last_name":"Bodensteiner","first_name":"J."},{"full_name":"Brands, S. A.","first_name":"S. A.","last_name":"Brands"},{"full_name":"Evans, C. J.","last_name":"Evans","first_name":"C. J."},{"first_name":"A.","last_name":"David-Uraz","full_name":"David-Uraz, A."},{"full_name":"Driessen, F. A.","first_name":"F. A.","last_name":"Driessen"},{"first_name":"K.","last_name":"Dsilva","full_name":"Dsilva, K."},{"full_name":"Geen, S.","first_name":"S.","last_name":"Geen"},{"full_name":"Gómez-González, V. M. A.","first_name":"V. M. A.","last_name":"Gómez-González"},{"full_name":"Grassitelli, L.","first_name":"L.","last_name":"Grassitelli"},{"last_name":"Hamann","first_name":"W.-R.","full_name":"Hamann, W.-R."},{"full_name":"Hawcroft, C.","first_name":"C.","last_name":"Hawcroft"},{"full_name":"Herrero, A.","last_name":"Herrero","first_name":"A."},{"full_name":"Higgins, E. R.","first_name":"E. R.","last_name":"Higgins"},{"full_name":"John Hillier, D.","first_name":"D.","last_name":"John Hillier"},{"full_name":"Ignace, R.","last_name":"Ignace","first_name":"R."},{"full_name":"Istrate, A. G.","first_name":"A. G.","last_name":"Istrate"},{"full_name":"Kaper, L.","first_name":"L.","last_name":"Kaper"},{"full_name":"Kee, N. D.","last_name":"Kee","first_name":"N. D."},{"last_name":"Kehrig","first_name":"C.","full_name":"Kehrig, C."},{"full_name":"Keszthelyi, Z.","last_name":"Keszthelyi","first_name":"Z."},{"last_name":"Klencki","first_name":"J.","full_name":"Klencki, J."},{"last_name":"de Koter","first_name":"A.","full_name":"de Koter, A."},{"full_name":"Kuiper, R.","first_name":"R.","last_name":"Kuiper"},{"full_name":"Laplace, E.","first_name":"E.","last_name":"Laplace"},{"full_name":"Larkin, C. J. K.","last_name":"Larkin","first_name":"C. J. K."},{"first_name":"R. R.","last_name":"Lefever","full_name":"Lefever, R. R."},{"full_name":"Leitherer, C.","first_name":"C.","last_name":"Leitherer"},{"full_name":"Lennon, D. J.","last_name":"Lennon","first_name":"D. J."},{"full_name":"Mahy, L.","first_name":"L.","last_name":"Mahy"},{"full_name":"Maíz Apellániz, J.","first_name":"J.","last_name":"Maíz Apellániz"},{"last_name":"Maravelias","first_name":"G.","full_name":"Maravelias, G."},{"first_name":"W.","last_name":"Marcolino","full_name":"Marcolino, W."},{"full_name":"McLeod, A. F.","last_name":"McLeod","first_name":"A. F."},{"first_name":"S. E.","last_name":"de Mink","full_name":"de Mink, S. E."},{"last_name":"Najarro","first_name":"F.","full_name":"Najarro, F."},{"full_name":"Oey, M. S.","first_name":"M. S.","last_name":"Oey"},{"last_name":"Parsons","first_name":"T. N.","full_name":"Parsons, T. N."},{"first_name":"D.","last_name":"Pauli","full_name":"Pauli, D."},{"first_name":"M. G.","last_name":"Pedersen","full_name":"Pedersen, M. G."},{"full_name":"Prinja, R. K.","last_name":"Prinja","first_name":"R. K."},{"first_name":"V.","last_name":"Ramachandran","full_name":"Ramachandran, V."},{"last_name":"Ramírez-Tannus","first_name":"M. C.","full_name":"Ramírez-Tannus, M. C."},{"first_name":"G. N.","last_name":"Sabhahit","full_name":"Sabhahit, G. N."},{"last_name":"Schootemeijer","first_name":"A.","full_name":"Schootemeijer, A."},{"full_name":"Reyero Serantes, S.","first_name":"S.","last_name":"Reyero Serantes"},{"full_name":"Shenar, T.","last_name":"Shenar","first_name":"T."},{"full_name":"Stringfellow, G. S.","last_name":"Stringfellow","first_name":"G. S."},{"full_name":"Sudnik, N.","last_name":"Sudnik","first_name":"N."},{"first_name":"F.","last_name":"Tramper","full_name":"Tramper, F."},{"first_name":"L.","last_name":"Wang","full_name":"Wang, L."}],"citation":{"mla":"Vink, Jorick S., et al. “X-Shooting ULLYSES: Massive Stars at Low Metallicity. I. Project Description.” <i>Astronomy &#38; Astrophysics</i>, vol. 675, A154, EDP Sciences, 2023, doi:<a href=\"https://doi.org/10.1051/0004-6361/202245650\">10.1051/0004-6361/202245650</a>.","ista":"Vink JS, Mehner A, Crowther PA, Fullerton A, Garcia M, Martins F, Morrell N, Oskinova LM, St-Louis N, ud-Doula A, Sander AAC, Sana H, Bouret J-C, Kubátová B, Marchant P, Martins LP, Wofford A, van Loon JT, Grace Telford O, Götberg YLL, Bowman DM, Erba C, Kalari VM, Abdul-Masih M, Alkousa T, Backs F, Barbosa CL, Berlanas SR, Bernini-Peron M, Bestenlehner JM, Blomme R, Bodensteiner J, Brands SA, Evans CJ, David-Uraz A, Driessen FA, Dsilva K, Geen S, Gómez-González VMA, Grassitelli L, Hamann W-R, Hawcroft C, Herrero A, Higgins ER, John Hillier D, Ignace R, Istrate AG, Kaper L, Kee ND, Kehrig C, Keszthelyi Z, Klencki J, de Koter A, Kuiper R, Laplace E, Larkin CJK, Lefever RR, Leitherer C, Lennon DJ, Mahy L, Maíz Apellániz J, Maravelias G, Marcolino W, McLeod AF, de Mink SE, Najarro F, Oey MS, Parsons TN, Pauli D, Pedersen MG, Prinja RK, Ramachandran V, Ramírez-Tannus MC, Sabhahit GN, Schootemeijer A, Reyero Serantes S, Shenar T, Stringfellow GS, Sudnik N, Tramper F, Wang L. 2023. X-shooting ULLYSES: Massive stars at low metallicity. I. Project description. Astronomy &#38; Astrophysics. 675, A154.","short":"J.S. Vink, A. Mehner, P.A. Crowther, A. Fullerton, M. Garcia, F. Martins, N. Morrell, L.M. Oskinova, N. St-Louis, A. ud-Doula, A.A.C. Sander, H. Sana, J.-C. Bouret, B. Kubátová, P. Marchant, L.P. Martins, A. Wofford, J.T. van Loon, O. Grace Telford, Y.L.L. Götberg, D.M. Bowman, C. Erba, V.M. Kalari, M. Abdul-Masih, T. Alkousa, F. Backs, C.L. Barbosa, S.R. Berlanas, M. Bernini-Peron, J.M. Bestenlehner, R. Blomme, J. Bodensteiner, S.A. Brands, C.J. Evans, A. David-Uraz, F.A. Driessen, K. Dsilva, S. Geen, V.M.A. Gómez-González, L. Grassitelli, W.-R. Hamann, C. Hawcroft, A. Herrero, E.R. Higgins, D. John Hillier, R. Ignace, A.G. Istrate, L. Kaper, N.D. Kee, C. Kehrig, Z. Keszthelyi, J. Klencki, A. de Koter, R. Kuiper, E. Laplace, C.J.K. Larkin, R.R. Lefever, C. Leitherer, D.J. Lennon, L. Mahy, J. Maíz Apellániz, G. Maravelias, W. Marcolino, A.F. McLeod, S.E. de Mink, F. Najarro, M.S. Oey, T.N. Parsons, D. Pauli, M.G. Pedersen, R.K. Prinja, V. Ramachandran, M.C. Ramírez-Tannus, G.N. Sabhahit, A. Schootemeijer, S. Reyero Serantes, T. Shenar, G.S. Stringfellow, N. Sudnik, F. Tramper, L. Wang, Astronomy &#38; Astrophysics 675 (2023).","ama":"Vink JS, Mehner A, Crowther PA, et al. X-shooting ULLYSES: Massive stars at low metallicity. I. Project description. <i>Astronomy &#38; Astrophysics</i>. 2023;675. doi:<a href=\"https://doi.org/10.1051/0004-6361/202245650\">10.1051/0004-6361/202245650</a>","chicago":"Vink, Jorick S., A. Mehner, P. A. Crowther, A. Fullerton, M. Garcia, F. Martins, N. Morrell, et al. “X-Shooting ULLYSES: Massive Stars at Low Metallicity. I. Project Description.” <i>Astronomy &#38; Astrophysics</i>. EDP Sciences, 2023. <a href=\"https://doi.org/10.1051/0004-6361/202245650\">https://doi.org/10.1051/0004-6361/202245650</a>.","apa":"Vink, J. S., Mehner, A., Crowther, P. A., Fullerton, A., Garcia, M., Martins, F., … Wang, L. (2023). X-shooting ULLYSES: Massive stars at low metallicity. I. Project description. <i>Astronomy &#38; Astrophysics</i>. EDP Sciences. <a href=\"https://doi.org/10.1051/0004-6361/202245650\">https://doi.org/10.1051/0004-6361/202245650</a>","ieee":"J. S. Vink <i>et al.</i>, “X-shooting ULLYSES: Massive stars at low metallicity. I. Project description,” <i>Astronomy &#38; Astrophysics</i>, vol. 675. EDP Sciences, 2023."},"publisher":"EDP Sciences","abstract":[{"text":"Observations of individual massive stars, super-luminous supernovae, gamma-ray bursts, and gravitational wave events involving spectacular black hole mergers indicate that the low-metallicity Universe is fundamentally different from our own Galaxy. Many transient phenomena will remain enigmatic until we achieve a firm understanding of the physics and evolution of massive stars at low metallicity (Z). The Hubble Space Telescope has devoted 500 orbits to observing ∼250 massive stars at low Z in the ultraviolet (UV) with the COS and STIS spectrographs under the ULLYSES programme. The complementary X-Shooting ULLYSES (XShootU) project provides an enhanced legacy value with high-quality optical and near-infrared spectra obtained with the wide-wavelength coverage X-shooter spectrograph at ESO’s Very Large Telescope. We present an overview of the XShootU project, showing that combining ULLYSES UV and XShootU optical spectra is critical for the uniform determination of stellar parameters such as effective temperature, surface gravity, luminosity, and abundances, as well as wind properties such as mass-loss rates as a function of Z. As uncertainties in stellar and wind parameters percolate into many adjacent areas of astrophysics, the data and modelling of the XShootU project is expected to be a game changer for our physical understanding of massive stars at low Z. To be able to confidently interpret James Webb Space Telescope spectra of the first stellar generations, the individual spectra of low-Z stars need to be understood, which is exactly where XShootU can deliver.","lang":"eng"}],"language":[{"iso":"eng"}],"oa":1},{"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","page":"1692-1709","keyword":["Space and Planetary Science","Astronomy and Astrophysics"],"scopus_import":"1","month":"09","arxiv":1,"date_published":"2023-09-01T00:00:00Z","publication":"Monthly Notices of the Royal Astronomical Society","external_id":{"arxiv":["2305.07337"]},"extern":"1","year":"2023","main_file_link":[{"url":"https://arxiv.org/abs/2305.07337","open_access":"1"}],"citation":{"apa":"Farmer, R., Renzo, M., Götberg, Y. L. L., Bellinger, E., Justham, S., &#38; de Mink, S. E. (2023). Observational predictions for Thorne–Żytkow objects. <i>Monthly Notices of the Royal Astronomical Society</i>. Oxford University Press. <a href=\"https://doi.org/10.1093/mnras/stad1977\">https://doi.org/10.1093/mnras/stad1977</a>","ieee":"R. Farmer, M. Renzo, Y. L. L. Götberg, E. Bellinger, S. Justham, and S. E. de Mink, “Observational predictions for Thorne–Żytkow objects,” <i>Monthly Notices of the Royal Astronomical Society</i>, vol. 524, no. 2. Oxford University Press, pp. 1692–1709, 2023.","ama":"Farmer R, Renzo M, Götberg YLL, Bellinger E, Justham S, de Mink SE. Observational predictions for Thorne–Żytkow objects. <i>Monthly Notices of the Royal Astronomical Society</i>. 2023;524(2):1692-1709. doi:<a href=\"https://doi.org/10.1093/mnras/stad1977\">10.1093/mnras/stad1977</a>","chicago":"Farmer, R, M Renzo, Ylva Louise Linsdotter Götberg, E Bellinger, S Justham, and S E de Mink. “Observational Predictions for Thorne–Żytkow Objects.” <i>Monthly Notices of the Royal Astronomical Society</i>. Oxford University Press, 2023. <a href=\"https://doi.org/10.1093/mnras/stad1977\">https://doi.org/10.1093/mnras/stad1977</a>.","short":"R. Farmer, M. Renzo, Y.L.L. Götberg, E. Bellinger, S. Justham, S.E. de Mink, Monthly Notices of the Royal Astronomical Society 524 (2023) 1692–1709.","ista":"Farmer R, Renzo M, Götberg YLL, Bellinger E, Justham S, de Mink SE. 2023. Observational predictions for Thorne–Żytkow objects. Monthly Notices of the Royal Astronomical Society. 524(2), 1692–1709.","mla":"Farmer, R., et al. “Observational Predictions for Thorne–Żytkow Objects.” <i>Monthly Notices of the Royal Astronomical Society</i>, vol. 524, no. 2, Oxford University Press, 2023, pp. 1692–709, doi:<a href=\"https://doi.org/10.1093/mnras/stad1977\">10.1093/mnras/stad1977</a>."},"publisher":"Oxford University Press","author":[{"last_name":"Farmer","first_name":"R","full_name":"Farmer, R"},{"last_name":"Renzo","first_name":"M","full_name":"Renzo, M"},{"id":"d0648d0c-0f64-11ee-a2e0-dd0faa2e4f7d","orcid":"0000-0002-6960-6911","full_name":"Götberg, Ylva Louise Linsdotter","first_name":"Ylva Louise Linsdotter","last_name":"Götberg"},{"full_name":"Bellinger, E","first_name":"E","last_name":"Bellinger"},{"last_name":"Justham","first_name":"S","full_name":"Justham, S"},{"full_name":"de Mink, S E","last_name":"de Mink","first_name":"S E"}],"day":"01","date_created":"2023-08-21T10:13:56Z","oa":1,"abstract":[{"lang":"eng","text":"Thorne–Żytkow objects (TŻO) are potential end products of the merger of a neutron star with a non-degenerate star. In this work, we have computed the first grid of evolutionary models of TŻOs with the MESA stellar evolution code. With these models, we predict several observational properties of TŻOs, including their surface temperatures and luminosities, pulsation periods, and nucleosynthetic products. We expand the range of possible TŻO solutions to cover 3.45≲log(Teff/K)≲3.65 and 4.85≲log(L/L⊙)≲5.5⁠. Due to the much higher densities our TŻOs reach compared to previous models, if TŻOs form we expect them to be stable over a larger mass range than previously predicted, without exhibiting a gap in their mass distribution. Using the GYRE stellar pulsation code we show that TŻOs should have fundamental pulsation periods of 1000–2000 d, and period ratios of ≈0.2–0.3. Models computed with a large 399 isotope fully coupled nuclear network show a nucleosynthetic signal that is different to previously predicted. We propose a new nucleosynthetic signal to determine a star’s status as a TŻO: the isotopologues 44TiO2 and 44TiO⁠, which will have a shift in their spectral features as compared to stable titanium-containing molecules. We find that in the local Universe (∼SMC metallicities and above) TŻOs show little heavy metal enrichment, potentially explaining the difficulty in finding TŻOs to-date."}],"language":[{"iso":"eng"}],"oa_version":"Preprint","status":"public","title":"Observational predictions for Thorne–Żytkow objects","date_updated":"2023-08-21T12:12:48Z","volume":524,"article_type":"original","fulldoi":"https://doi.org/10.1093/mnras/stad1977","quality_controlled":"1","article_processing_charge":"No","_id":"14104","issue":"2","intvolume":"       524","publication_identifier":{"issn":["0035-8711"],"eissn":["1365-2966"]},"publication_status":"published","doi":"10.1093/mnras/stad1977","type":"journal_article"},{"oa_version":"Preprint","status":"public","title":"TeST: Test-time Self-Training under distribution shift","date_updated":"2023-09-06T10:26:56Z","main_file_link":[{"url":"https://arxiv.org/abs/2209.11459","open_access":"1"}],"citation":{"ama":"Sinha S, Gehler P, Locatello F, Schiele B. TeST: Test-time Self-Training under distribution shift. In: <i>2023 IEEE/CVF Winter Conference on Applications of Computer Vision</i>. Institute of Electrical and Electronics Engineers; 2023. doi:<a href=\"https://doi.org/10.1109/wacv56688.2023.00278\">10.1109/wacv56688.2023.00278</a>","chicago":"Sinha, Samarth, Peter Gehler, Francesco Locatello, and Bernt Schiele. “TeST: Test-Time Self-Training under Distribution Shift.” In <i>2023 IEEE/CVF Winter Conference on Applications of Computer Vision</i>. Institute of Electrical and Electronics Engineers, 2023. <a href=\"https://doi.org/10.1109/wacv56688.2023.00278\">https://doi.org/10.1109/wacv56688.2023.00278</a>.","short":"S. Sinha, P. Gehler, F. Locatello, B. Schiele, in:, 2023 IEEE/CVF Winter Conference on Applications of Computer Vision, Institute of Electrical and Electronics Engineers, 2023.","ista":"Sinha S, Gehler P, Locatello F, Schiele B. 2023. TeST: Test-time Self-Training under distribution shift. 2023 IEEE/CVF Winter Conference on Applications of Computer Vision. WACV: Winter Conference on Applications of Computer Vision.","mla":"Sinha, Samarth, et al. “TeST: Test-Time Self-Training under Distribution Shift.” <i>2023 IEEE/CVF Winter Conference on Applications of Computer Vision</i>, Institute of Electrical and Electronics Engineers, 2023, doi:<a href=\"https://doi.org/10.1109/wacv56688.2023.00278\">10.1109/wacv56688.2023.00278</a>.","ieee":"S. Sinha, P. Gehler, F. Locatello, and B. Schiele, “TeST: Test-time Self-Training under distribution shift,” in <i>2023 IEEE/CVF Winter Conference on Applications of Computer Vision</i>, Waikoloa, HI, United States, 2023.","apa":"Sinha, S., Gehler, P., Locatello, F., &#38; Schiele, B. (2023). TeST: Test-time Self-Training under distribution shift. In <i>2023 IEEE/CVF Winter Conference on Applications of Computer Vision</i>. Waikoloa, HI, United States: Institute of Electrical and Electronics Engineers. <a href=\"https://doi.org/10.1109/wacv56688.2023.00278\">https://doi.org/10.1109/wacv56688.2023.00278</a>"},"author":[{"first_name":"Samarth","last_name":"Sinha","full_name":"Sinha, Samarth"},{"full_name":"Gehler, Peter","last_name":"Gehler","first_name":"Peter"},{"full_name":"Locatello, Francesco","id":"26cfd52f-2483-11ee-8040-88983bcc06d4","orcid":"0000-0002-4850-0683","last_name":"Locatello","first_name":"Francesco"},{"full_name":"Schiele, Bernt","last_name":"Schiele","first_name":"Bernt"}],"publisher":"Institute of Electrical and Electronics Engineers","day":"06","date_created":"2023-08-21T12:11:38Z","oa":1,"abstract":[{"text":"Despite their recent success, deep neural networks continue to perform poorly when they encounter distribution shifts at test time. Many recently proposed approaches try to counter this by aligning the model to the new distribution prior to inference. With no labels available this requires unsupervised objectives to adapt the model on the observed test data. In this paper, we propose Test-Time SelfTraining (TeST): a technique that takes as input a model trained on some source data and a novel data distribution at test time, and learns invariant and robust representations using a student-teacher framework. We find that models adapted using TeST significantly improve over baseline testtime adaptation algorithms. TeST achieves competitive performance to modern domain adaptation algorithms [4, 43], while having access to 5-10x less data at time of adaption. We thoroughly evaluate a variety of baselines on two tasks:\r\nobject detection and image segmentation and find that models adapted with TeST. We find that TeST sets the new stateof-the art for test-time domain adaptation algorithms. ","lang":"eng"}],"language":[{"iso":"eng"}],"department":[{"_id":"FrLo"}],"publication":"2023 IEEE/CVF Winter Conference on Applications of Computer Vision","external_id":{"arxiv":["2209.11459"]},"conference":{"location":"Waikoloa, HI, United States","start_date":"2023-01-02","name":"WACV: Winter Conference on Applications of Computer Vision","end_date":"2023-01-07"},"extern":"1","year":"2023","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","scopus_import":"1","month":"02","arxiv":1,"date_published":"2023-02-06T00:00:00Z","publication_status":"published","doi":"10.1109/wacv56688.2023.00278","type":"conference","_id":"14105","publication_identifier":{"eissn":["2642-9381"],"isbn":["9781665493475"]},"quality_controlled":"1","article_processing_charge":"No","fulldoi":"https://doi.org/10.1109/wacv56688.2023.00278"},{"doi":"10.1007/s11040-023-09460-x","type":"journal_article","publication_status":"published","publication_identifier":{"issn":["1385-0172"],"eissn":["1572-9656"]},"issue":"3","_id":"14192","article_number":"17","intvolume":"        26","article_processing_charge":"Yes (via OA deal)","quality_controlled":"1","has_accepted_license":"1","file_date_updated":"2023-08-23T10:59:15Z","fulldoi":"https://doi.org/10.1007/s11040-023-09460-x","article_type":"original","isi":1,"corr_author":"1","title":"On the global minimum of the energy–momentum relation for the polaron","tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","image":"/images/cc_by.png","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)"},"status":"public","volume":26,"date_updated":"2024-10-09T21:06:41Z","oa_version":"Published Version","ddc":["510"],"oa":1,"department":[{"_id":"RoSe"}],"language":[{"iso":"eng"}],"abstract":[{"text":"For the Fröhlich model of the large polaron, we prove that the ground state energy as a function of the total momentum has a unique global minimum at momentum zero. This implies the non-existence of a ground state of the translation invariant Fröhlich Hamiltonian and thus excludes the possibility of a localization transition at finite coupling.","lang":"eng"}],"citation":{"chicago":"Lampart, Jonas, David Johannes Mitrouskas, and Krzysztof Mysliwy. “On the Global Minimum of the Energy–Momentum Relation for the Polaron.” <i>Mathematical Physics, Analysis and Geometry</i>. Springer Nature, 2023. <a href=\"https://doi.org/10.1007/s11040-023-09460-x\">https://doi.org/10.1007/s11040-023-09460-x</a>.","ama":"Lampart J, Mitrouskas DJ, Mysliwy K. On the global minimum of the energy–momentum relation for the polaron. <i>Mathematical Physics, Analysis and Geometry</i>. 2023;26(3). doi:<a href=\"https://doi.org/10.1007/s11040-023-09460-x\">10.1007/s11040-023-09460-x</a>","short":"J. Lampart, D.J. Mitrouskas, K. Mysliwy, Mathematical Physics, Analysis and Geometry 26 (2023).","ista":"Lampart J, Mitrouskas DJ, Mysliwy K. 2023. On the global minimum of the energy–momentum relation for the polaron. Mathematical Physics, Analysis and Geometry. 26(3), 17.","mla":"Lampart, Jonas, et al. “On the Global Minimum of the Energy–Momentum Relation for the Polaron.” <i>Mathematical Physics, Analysis and Geometry</i>, vol. 26, no. 3, 17, Springer Nature, 2023, doi:<a href=\"https://doi.org/10.1007/s11040-023-09460-x\">10.1007/s11040-023-09460-x</a>.","apa":"Lampart, J., Mitrouskas, D. J., &#38; Mysliwy, K. (2023). On the global minimum of the energy–momentum relation for the polaron. <i>Mathematical Physics, Analysis and Geometry</i>. Springer Nature. <a href=\"https://doi.org/10.1007/s11040-023-09460-x\">https://doi.org/10.1007/s11040-023-09460-x</a>","ieee":"J. Lampart, D. J. Mitrouskas, and K. Mysliwy, “On the global minimum of the energy–momentum relation for the polaron,” <i>Mathematical Physics, Analysis and Geometry</i>, vol. 26, no. 3. Springer Nature, 2023."},"publisher":"Springer Nature","author":[{"full_name":"Lampart, Jonas","first_name":"Jonas","last_name":"Lampart"},{"id":"cbddacee-2b11-11eb-a02e-a2e14d04e52d","full_name":"Mitrouskas, David Johannes","last_name":"Mitrouskas","first_name":"David Johannes"},{"id":"316457FC-F248-11E8-B48F-1D18A9856A87","full_name":"Mysliwy, Krzysztof","last_name":"Mysliwy","first_name":"Krzysztof"}],"date_created":"2023-08-22T14:09:47Z","day":"26","year":"2023","publication":"Mathematical Physics, Analysis and Geometry","file":[{"file_name":"2023_MathPhysics_Lampart.pdf","content_type":"application/pdf","relation":"main_file","file_size":317026,"date_updated":"2023-08-23T10:59:15Z","file_id":"14225","creator":"dernst","date_created":"2023-08-23T10:59:15Z","success":1,"access_level":"open_access","checksum":"f0941cc66cb3ed06a12ca4b7e356cfd6"}],"external_id":{"isi":["001032992600001"],"arxiv":["2206.14708"]},"date_published":"2023-07-26T00:00:00Z","month":"07","arxiv":1,"scopus_import":"1","acknowledgement":"D.M. and K.M. thank Robert Seiringer for helpful discussions. Open access funding provided by Institute of Science and Technology (IST Austria). Financial support from the Agence Nationale de la Recherche (ANR) through the projects ANR-17-CE40-0016, ANR-17-CE40-0007-01, ANR-17-EURE-0002 (J.L.) and from the European Union’s Horizon 2020 research and innovation programme under the Maria Skłodowska-Curie grant agreement No. 665386 (K.M.) is gratefully acknowledged.","keyword":["Geometry and Topology","Mathematical Physics"],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87"},{"article_processing_charge":"No","quality_controlled":"1","_id":"14208","intvolume":"       202","type":"conference","publication_status":"published","alternative_title":["PMLR"],"page":"43105-43128","month":"05","arxiv":1,"date_published":"2023-05-30T00:00:00Z","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","extern":"1","year":"2023","publication":"Proceedings of the 40th International Conference on Machine Learning","external_id":{"arxiv":["2305.19377"]},"conference":{"location":"Honolulu, Hawaii, United States","end_date":"2023-07-29","name":"International Conference on Machine Learning","start_date":"2023-07-23"},"oa":1,"abstract":[{"text":"This paper focuses on over-parameterized deep neural networks (DNNs) with ReLU activation functions and proves that when the data distribution is well-separated, DNNs can achieve Bayes-optimal test error for classification while obtaining (nearly) zero-training error under the lazy training regime. For this purpose, we unify three interrelated concepts of overparameterization, benign overfitting, and the Lipschitz constant of DNNs. Our results indicate that interpolating with smoother functions leads to better generalization. Furthermore, we investigate the special case where interpolating smooth ground-truth functions is performed by DNNs under the Neural Tangent Kernel (NTK) regime for generalization. Our result demonstrates that the generalization error converges to a constant order that only depends on label noise and initialization noise, which theoretically verifies benign overfitting. Our analysis provides a tight lower bound on the normalized margin under non-smooth activation functions, as well as the minimum eigenvalue of NTK under high-dimensional settings, which has its own interest in learning theory.","lang":"eng"}],"department":[{"_id":"FrLo"}],"language":[{"iso":"eng"}],"main_file_link":[{"url":"https://doi.org/10.48550/arXiv.2305.19377","open_access":"1"}],"author":[{"first_name":"Zhenyu","last_name":"Zhu","full_name":"Zhu, Zhenyu"},{"first_name":"Fanghui","last_name":"Liu","full_name":"Liu, Fanghui"},{"full_name":"Chrysos, Grigorios G","last_name":"Chrysos","first_name":"Grigorios G"},{"id":"26cfd52f-2483-11ee-8040-88983bcc06d4","orcid":"0000-0002-4850-0683","full_name":"Locatello, Francesco","last_name":"Locatello","first_name":"Francesco"},{"full_name":"Cevher, Volkan","first_name":"Volkan","last_name":"Cevher"}],"publisher":"ML Research Press","citation":{"short":"Z. Zhu, F. Liu, G.G. Chrysos, F. Locatello, V. Cevher, in:, Proceedings of the 40th International Conference on Machine Learning, ML Research Press, 2023, pp. 43105–43128.","ama":"Zhu Z, Liu F, Chrysos GG, Locatello F, Cevher V. Benign overfitting in deep neural networks under lazy training. In: <i>Proceedings of the 40th International Conference on Machine Learning</i>. Vol 202. ML Research Press; 2023:43105-43128.","chicago":"Zhu, Zhenyu, Fanghui Liu, Grigorios G Chrysos, Francesco Locatello, and Volkan Cevher. “Benign Overfitting in Deep Neural Networks under Lazy Training.” In <i>Proceedings of the 40th International Conference on Machine Learning</i>, 202:43105–28. ML Research Press, 2023.","mla":"Zhu, Zhenyu, et al. “Benign Overfitting in Deep Neural Networks under Lazy Training.” <i>Proceedings of the 40th International Conference on Machine Learning</i>, vol. 202, ML Research Press, 2023, pp. 43105–28.","ista":"Zhu Z, Liu F, Chrysos GG, Locatello F, Cevher V. 2023. Benign overfitting in deep neural networks under lazy training. Proceedings of the 40th International Conference on Machine Learning. International Conference on Machine Learning, PMLR, vol. 202, 43105–43128.","apa":"Zhu, Z., Liu, F., Chrysos, G. G., Locatello, F., &#38; Cevher, V. (2023). Benign overfitting in deep neural networks under lazy training. In <i>Proceedings of the 40th International Conference on Machine Learning</i> (Vol. 202, pp. 43105–43128). Honolulu, Hawaii, United States: ML Research Press.","ieee":"Z. Zhu, F. Liu, G. G. Chrysos, F. Locatello, and V. Cevher, “Benign overfitting in deep neural networks under lazy training,” in <i>Proceedings of the 40th International Conference on Machine Learning</i>, Honolulu, Hawaii, United States, 2023, vol. 202, pp. 43105–43128."},"day":"30","date_created":"2023-08-22T14:18:18Z","status":"public","title":"Benign overfitting in deep neural networks under lazy training","volume":202,"date_updated":"2023-09-13T08:46:46Z","oa_version":"Preprint"},{"external_id":{"arxiv":["2304.10253"]},"publication":"arXiv","article_processing_charge":"No","extern":"1","year":"2023","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","arxiv":1,"date_published":"2023-04-20T00:00:00Z","month":"04","fulldoi":"https://doi.org/10.48550/arXiv.2304.10253","oa_version":"Preprint","publication_status":"submitted","date_updated":"2023-09-13T08:51:56Z","type":"preprint","doi":"10.48550/arXiv.2304.10253","status":"public","title":"A data augmentation perspective on diffusion models and retrieval","day":"20","article_number":"2304.10253","date_created":"2023-08-22T14:18:43Z","main_file_link":[{"open_access":"1","url":"https://doi.org/10.48550/arXiv.2304.10253"}],"_id":"14209","citation":{"short":"M.F. Burg, F. Wenzel, D. Zietlow, M. Horn, O. Makansi, F. Locatello, C. Russell, ArXiv (n.d.).","ama":"Burg MF, Wenzel F, Zietlow D, et al. A data augmentation perspective on diffusion models and retrieval. <i>arXiv</i>. doi:<a href=\"https://doi.org/10.48550/arXiv.2304.10253\">10.48550/arXiv.2304.10253</a>","chicago":"Burg, Max F., Florian Wenzel, Dominik Zietlow, Max Horn, Osama Makansi, Francesco Locatello, and Chris Russell. “A Data Augmentation Perspective on Diffusion Models and Retrieval.” <i>ArXiv</i>, n.d. <a href=\"https://doi.org/10.48550/arXiv.2304.10253\">https://doi.org/10.48550/arXiv.2304.10253</a>.","ista":"Burg MF, Wenzel F, Zietlow D, Horn M, Makansi O, Locatello F, Russell C. A data augmentation perspective on diffusion models and retrieval. arXiv, 2304.10253.","mla":"Burg, Max F., et al. “A Data Augmentation Perspective on Diffusion Models and Retrieval.” <i>ArXiv</i>, 2304.10253, doi:<a href=\"https://doi.org/10.48550/arXiv.2304.10253\">10.48550/arXiv.2304.10253</a>.","apa":"Burg, M. F., Wenzel, F., Zietlow, D., Horn, M., Makansi, O., Locatello, F., &#38; Russell, C. (n.d.). A data augmentation perspective on diffusion models and retrieval. <i>arXiv</i>. <a href=\"https://doi.org/10.48550/arXiv.2304.10253\">https://doi.org/10.48550/arXiv.2304.10253</a>","ieee":"M. F. Burg <i>et al.</i>, “A data augmentation perspective on diffusion models and retrieval,” <i>arXiv</i>. ."},"author":[{"first_name":"Max F.","last_name":"Burg","full_name":"Burg, Max F."},{"last_name":"Wenzel","first_name":"Florian","full_name":"Wenzel, Florian"},{"full_name":"Zietlow, Dominik","last_name":"Zietlow","first_name":"Dominik"},{"first_name":"Max","last_name":"Horn","full_name":"Horn, Max"},{"full_name":"Makansi, Osama","last_name":"Makansi","first_name":"Osama"},{"orcid":"0000-0002-4850-0683","id":"26cfd52f-2483-11ee-8040-88983bcc06d4","full_name":"Locatello, Francesco","last_name":"Locatello","first_name":"Francesco"},{"last_name":"Russell","first_name":"Chris","full_name":"Russell, Chris"}],"abstract":[{"lang":"eng","text":"Diffusion models excel at generating photorealistic images from text-queries. Naturally, many approaches have been proposed to use these generative abilities to augment training datasets for downstream tasks, such as classification. However, diffusion models are themselves trained on large noisily supervised, but nonetheless, annotated datasets. It is an open question whether the generalization capabilities of diffusion models beyond using the additional data of the pre-training process for augmentation lead to improved downstream performance. We perform a systematic evaluation of existing methods to generate images from diffusion models and study new extensions to assess their benefit for data augmentation. While we find that personalizing diffusion models towards the target data outperforms simpler prompting strategies, we also show that using the training data of the diffusion model alone, via a simple nearest neighbor retrieval procedure, leads to even stronger downstream performance. Overall, our study probes the limitations of diffusion models for data augmentation but also highlights its potential in generating new training data to improve performance on simple downstream vision tasks."}],"language":[{"iso":"eng"}],"department":[{"_id":"FrLo"}],"oa":1},{"date_created":"2023-08-22T14:19:21Z","day":"01","citation":{"chicago":"Montagna, Francesco, Nicoletta Noceti, Lorenzo Rosasco, Kun Zhang, and Francesco Locatello. “Causal Discovery with Score Matching on Additive Models with Arbitrary Noise.” In <i>2nd Conference on Causal Learning and Reasoning</i>, 2023.","ama":"Montagna F, Noceti N, Rosasco L, Zhang K, Locatello F. Causal discovery with score matching on additive models with arbitrary noise. In: <i>2nd Conference on Causal Learning and Reasoning</i>. ; 2023.","short":"F. Montagna, N. Noceti, L. Rosasco, K. Zhang, F. Locatello, in:, 2nd Conference on Causal Learning and Reasoning, 2023.","mla":"Montagna, Francesco, et al. “Causal Discovery with Score Matching on Additive Models with Arbitrary Noise.” <i>2nd Conference on Causal Learning and Reasoning</i>, 2023.","ista":"Montagna F, Noceti N, Rosasco L, Zhang K, Locatello F. 2023. Causal discovery with score matching on additive models with arbitrary noise. 2nd Conference on Causal Learning and Reasoning. CLeaR: Conference on Causal Learning and Reasoning.","ieee":"F. Montagna, N. Noceti, L. Rosasco, K. Zhang, and F. Locatello, “Causal discovery with score matching on additive models with arbitrary noise,” in <i>2nd Conference on Causal Learning and Reasoning</i>, Tübingen, Germany, 2023.","apa":"Montagna, F., Noceti, N., Rosasco, L., Zhang, K., &#38; Locatello, F. (2023). Causal discovery with score matching on additive models with arbitrary noise. In <i>2nd Conference on Causal Learning and Reasoning</i>. Tübingen, Germany."},"author":[{"full_name":"Montagna, Francesco","last_name":"Montagna","first_name":"Francesco"},{"first_name":"Nicoletta","last_name":"Noceti","full_name":"Noceti, Nicoletta"},{"full_name":"Rosasco, Lorenzo","last_name":"Rosasco","first_name":"Lorenzo"},{"first_name":"Kun","last_name":"Zhang","full_name":"Zhang, Kun"},{"full_name":"Locatello, Francesco","id":"26cfd52f-2483-11ee-8040-88983bcc06d4","orcid":"0000-0002-4850-0683","first_name":"Francesco","last_name":"Locatello"}],"main_file_link":[{"url":"https://arxiv.org/abs/2304.03265","open_access":"1"}],"_id":"14211","language":[{"iso":"eng"}],"department":[{"_id":"FrLo"}],"abstract":[{"lang":"eng","text":"Causal discovery methods are intrinsically constrained by the set of assumptions needed to ensure structure identifiability. Moreover additional restrictions are often imposed in order to simplify the inference task: this is the case for the Gaussian noise assumption on additive non-linear models, which is common to many causal discovery approaches. In this paper we show the shortcomings of inference under this hypothesis, analyzing the risk of edge inversion under violation of Gaussianity of the noise terms. Then, we propose a novel method for inferring the topological ordering of the variables in the causal graph, from data generated according to an additive non-linear model with a generic noise distribution. This leads to NoGAM (Not only Gaussian Additive noise Models), a causal discovery algorithm with a minimal set of assumptions and state of the art performance, experimentally benchmarked on synthetic data."}],"oa":1,"oa_version":"Preprint","publication_status":"published","date_updated":"2024-10-14T12:30:04Z","type":"conference","status":"public","title":"Causal discovery with score matching on additive models with arbitrary noise","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","date_published":"2023-04-01T00:00:00Z","month":"04","arxiv":1,"scopus_import":"1","conference":{"end_date":"2023-04-14","name":"CLeaR: Conference on Causal Learning and Reasoning","start_date":"2023-04-11","location":"Tübingen, Germany"},"external_id":{"arxiv":["2304.03265"]},"quality_controlled":"1","publication":"2nd Conference on Causal Learning and Reasoning","year":"2023","article_processing_charge":"No","extern":"1"},{"quality_controlled":"1","publication":"2nd Conference on Causal Learning and Reasoning","conference":{"name":"CLeaR: Conference on Causal Learning and Reasoning","start_date":"2023-04-11","end_date":"2023-04-14","location":"Tübingen, Germany"},"external_id":{"arxiv":["2304.03382"]},"year":"2023","article_processing_charge":"No","extern":"1","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","date_published":"2023-04-01T00:00:00Z","arxiv":1,"month":"04","scopus_import":"1","publication_status":"published","oa_version":"Preprint","status":"public","title":"Scalable causal discovery with score matching","type":"conference","date_updated":"2024-10-14T12:30:15Z","citation":{"apa":"Montagna, F., Noceti, N., Rosasco, L., Zhang, K., &#38; Locatello, F. (2023). Scalable causal discovery with score matching. In <i>2nd Conference on Causal Learning and Reasoning</i>. Tübingen, Germany.","ieee":"F. Montagna, N. Noceti, L. Rosasco, K. Zhang, and F. Locatello, “Scalable causal discovery with score matching,” in <i>2nd Conference on Causal Learning and Reasoning</i>, Tübingen, Germany, 2023.","mla":"Montagna, Francesco, et al. “Scalable Causal Discovery with Score Matching.” <i>2nd Conference on Causal Learning and Reasoning</i>, 2023.","ista":"Montagna F, Noceti N, Rosasco L, Zhang K, Locatello F. 2023. Scalable causal discovery with score matching. 2nd Conference on Causal Learning and Reasoning. CLeaR: Conference on Causal Learning and Reasoning.","ama":"Montagna F, Noceti N, Rosasco L, Zhang K, Locatello F. Scalable causal discovery with score matching. In: <i>2nd Conference on Causal Learning and Reasoning</i>. ; 2023.","short":"F. Montagna, N. Noceti, L. Rosasco, K. Zhang, F. Locatello, in:, 2nd Conference on Causal Learning and Reasoning, 2023.","chicago":"Montagna, Francesco, Nicoletta Noceti, Lorenzo Rosasco, Kun Zhang, and Francesco Locatello. “Scalable Causal Discovery with Score Matching.” In <i>2nd Conference on Causal Learning and Reasoning</i>, 2023."},"author":[{"full_name":"Montagna, Francesco","first_name":"Francesco","last_name":"Montagna"},{"last_name":"Noceti","first_name":"Nicoletta","full_name":"Noceti, Nicoletta"},{"last_name":"Rosasco","first_name":"Lorenzo","full_name":"Rosasco, Lorenzo"},{"full_name":"Zhang, Kun","last_name":"Zhang","first_name":"Kun"},{"last_name":"Locatello","first_name":"Francesco","full_name":"Locatello, Francesco","id":"26cfd52f-2483-11ee-8040-88983bcc06d4","orcid":"0000-0002-4850-0683"}],"main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/2304.03382"}],"_id":"14212","date_created":"2023-08-22T14:19:40Z","day":"01","oa":1,"language":[{"iso":"eng"}],"department":[{"_id":"FrLo"}],"abstract":[{"lang":"eng","text":"This paper demonstrates how to discover the whole causal graph from the second derivative of the log-likelihood in observational non-linear additive Gaussian noise models. Leveraging scalable machine learning approaches to approximate the score function ∇logp(X), we extend the work of Rolland et al. (2022) that only recovers the topological order from the score and requires an expensive pruning step removing spurious edges among those admitted by the ordering. Our analysis leads to DAS (acronym for Discovery At Scale), a practical algorithm that reduces the complexity of the pruning by a factor proportional to the graph size. In practice, DAS achieves competitive accuracy with current state-of-the-art while being over an order of magnitude faster. Overall, our approach enables principled and scalable causal discovery, significantly lowering the compute bar."}]},{"day":"12","date_created":"2023-08-22T14:20:18Z","main_file_link":[{"url":"https://doi.org/10.48550/arXiv.2301.05169","open_access":"1"}],"_id":"14214","citation":{"apa":"Liu, Y., Alahi, A., Russell, C., Horn, M., Zietlow, D., Schölkopf, B., &#38; Locatello, F. (2023). Causal triplet: An open challenge for intervention-centric causal representation learning. In <i>2nd Conference on Causal Learning and Reasoning</i>. Tübingen, Germany.","ieee":"Y. Liu <i>et al.</i>, “Causal triplet: An open challenge for intervention-centric causal representation learning,” in <i>2nd Conference on Causal Learning and Reasoning</i>, Tübingen, Germany, 2023.","chicago":"Liu, Yuejiang, Alexandre Alahi, Chris Russell, Max Horn, Dominik Zietlow, Bernhard Schölkopf, and Francesco Locatello. “Causal Triplet: An Open Challenge for Intervention-Centric Causal Representation Learning.” In <i>2nd Conference on Causal Learning and Reasoning</i>, 2023.","short":"Y. Liu, A. Alahi, C. Russell, M. Horn, D. Zietlow, B. Schölkopf, F. Locatello, in:, 2nd Conference on Causal Learning and Reasoning, 2023.","ama":"Liu Y, Alahi A, Russell C, et al. Causal triplet: An open challenge for intervention-centric causal representation learning. In: <i>2nd Conference on Causal Learning and Reasoning</i>. ; 2023.","mla":"Liu, Yuejiang, et al. “Causal Triplet: An Open Challenge for Intervention-Centric Causal Representation Learning.” <i>2nd Conference on Causal Learning and Reasoning</i>, 2023.","ista":"Liu Y, Alahi A, Russell C, Horn M, Zietlow D, Schölkopf B, Locatello F. 2023. Causal triplet: An open challenge for intervention-centric causal representation learning. 2nd Conference on Causal Learning and Reasoning. CLeaR: Conference on Causal Learning and Reasoning."},"author":[{"last_name":"Liu","first_name":"Yuejiang","full_name":"Liu, Yuejiang"},{"last_name":"Alahi","first_name":"Alexandre","full_name":"Alahi, Alexandre"},{"full_name":"Russell, Chris","first_name":"Chris","last_name":"Russell"},{"full_name":"Horn, Max","last_name":"Horn","first_name":"Max"},{"full_name":"Zietlow, Dominik","last_name":"Zietlow","first_name":"Dominik"},{"first_name":"Bernhard","last_name":"Schölkopf","full_name":"Schölkopf, Bernhard"},{"first_name":"Francesco","last_name":"Locatello","orcid":"0000-0002-4850-0683","id":"26cfd52f-2483-11ee-8040-88983bcc06d4","full_name":"Locatello, Francesco"}],"abstract":[{"lang":"eng","text":"Recent years have seen a surge of interest in learning high-level causal representations from low-level image pairs under interventions. Yet, existing efforts are largely limited to simple synthetic settings that are far away from real-world problems. In this paper, we present Causal Triplet, a causal representation learning benchmark featuring not only visually more complex scenes, but also two crucial desiderata commonly overlooked in previous works: (i) an actionable counterfactual setting, where only certain object-level variables allow for counterfactual observations whereas others do not; (ii) an interventional downstream task with an emphasis on out-of-distribution robustness from the independent causal mechanisms principle. Through extensive experiments, we find that models built with the knowledge of disentangled or object-centric representations significantly outperform their distributed counterparts. However, recent causal representation learning methods still struggle to identify such latent structures, indicating substantial challenges and opportunities for future work."}],"language":[{"iso":"eng"}],"department":[{"_id":"FrLo"}],"oa":1,"publication_status":"published","oa_version":"Preprint","date_updated":"2024-10-14T12:30:42Z","type":"conference","status":"public","title":"Causal triplet: An open challenge for intervention-centric causal representation learning","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","arxiv":1,"date_published":"2023-04-12T00:00:00Z","month":"04","external_id":{"arxiv":["2301.05169"]},"conference":{"end_date":"2023-04-14","name":"CLeaR: Conference on Causal Learning and Reasoning","start_date":"2023-04-11","location":"Tübingen, Germany"},"publication":"2nd Conference on Causal Learning and Reasoning","quality_controlled":"1","article_processing_charge":"No","extern":"1","year":"2023"},{"title":"ASIF: Coupled data turns unimodal models to multimodal without training","status":"public","volume":36,"date_updated":"2025-05-14T11:28:52Z","oa_version":"Preprint","ddc":["000"],"oa":1,"abstract":[{"lang":"eng","text":"CLIP proved that aligning visual and language spaces is key to solving many vision tasks without explicit training, but required to train image and text encoders from scratch on a huge dataset. LiT improved this by only training the text encoder and using a pre-trained vision network. In this paper, we show that a common space can be created without any training at all, using single-domain encoders (trained with or without supervision) and a much smaller amount of image-text pairs. Furthermore, our model has unique properties. Most notably, deploying a new version with updated training samples can be done in a matter of seconds. Additionally, the representations in the common space are easily interpretable as every dimension corresponds to the similarity of the input to a unique entry in the multimodal dataset. Experiments on standard zero-shot visual benchmarks demonstrate the typical transfer ability of image-text models. Overall, our method represents a simple yet surprisingly strong baseline for foundation multi-modal models, raising important questions on their data efficiency and on the role of retrieval in machine learning."}],"language":[{"iso":"eng"}],"department":[{"_id":"FrLo"}],"author":[{"full_name":"Norelli, Antonio","last_name":"Norelli","first_name":"Antonio"},{"first_name":"Marco","last_name":"Fumero","full_name":"Fumero, Marco"},{"first_name":"Valentino","last_name":"Maiorca","full_name":"Maiorca, Valentino"},{"full_name":"Moschella, Luca","last_name":"Moschella","first_name":"Luca"},{"full_name":"Rodolà, Emanuele","first_name":"Emanuele","last_name":"Rodolà"},{"last_name":"Locatello","first_name":"Francesco","full_name":"Locatello, Francesco","orcid":"0000-0002-4850-0683","id":"26cfd52f-2483-11ee-8040-88983bcc06d4"}],"citation":{"short":"A. Norelli, M. Fumero, V. Maiorca, L. Moschella, E. Rodolà, F. Locatello, in:, 37th Conference on Neural Information Processing Systems, Neural Information Processing Systems Foundation, 2023, pp. 15303–15319.","chicago":"Norelli, Antonio, Marco Fumero, Valentino Maiorca, Luca Moschella, Emanuele Rodolà, and Francesco Locatello. “ASIF: Coupled Data Turns Unimodal Models to Multimodal without Training.” In <i>37th Conference on Neural Information Processing Systems</i>, 36:15303–19. Neural Information Processing Systems Foundation, 2023.","ama":"Norelli A, Fumero M, Maiorca V, Moschella L, Rodolà E, Locatello F. ASIF: Coupled data turns unimodal models to multimodal without training. In: <i>37th Conference on Neural Information Processing Systems</i>. Vol 36. Neural Information Processing Systems Foundation; 2023:15303-15319.","ista":"Norelli A, Fumero M, Maiorca V, Moschella L, Rodolà E, Locatello F. 2023. ASIF: Coupled data turns unimodal models to multimodal without training. 37th Conference on Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems, Advances in Neural Information Processing Systems, vol. 36, 15303–15319.","mla":"Norelli, Antonio, et al. “ASIF: Coupled Data Turns Unimodal Models to Multimodal without Training.” <i>37th Conference on Neural Information Processing Systems</i>, vol. 36, Neural Information Processing Systems Foundation, 2023, pp. 15303–19.","apa":"Norelli, A., Fumero, M., Maiorca, V., Moschella, L., Rodolà, E., &#38; Locatello, F. (2023). ASIF: Coupled data turns unimodal models to multimodal without training. In <i>37th Conference on Neural Information Processing Systems</i> (Vol. 36, pp. 15303–15319). New Orleans, LA, United States: Neural Information Processing Systems Foundation.","ieee":"A. Norelli, M. Fumero, V. Maiorca, L. Moschella, E. Rodolà, and F. Locatello, “ASIF: Coupled data turns unimodal models to multimodal without training,” in <i>37th Conference on Neural Information Processing Systems</i>, New Orleans, LA, United States, 2023, vol. 36, pp. 15303–15319."},"publisher":"Neural Information Processing Systems Foundation","day":"04","date_created":"2023-08-22T14:22:04Z","year":"2023","file":[{"date_created":"2025-02-04T12:16:13Z","success":1,"access_level":"open_access","checksum":"e51c90300b92d7135050da5c9e3a8015","file_name":"2023_NeurIPS_Fumero.pdf","content_type":"application/pdf","relation":"main_file","date_updated":"2025-02-04T12:16:13Z","file_size":12648978,"creator":"dernst","file_id":"18994"}],"publication":"37th Conference on Neural Information Processing Systems","external_id":{"arxiv":["2210.01738"]},"conference":{"location":"New Orleans, LA, United States","end_date":"2023-12-14","start_date":"2023-12-12","name":"NeurIPS: Neural Information Processing Systems"},"page":"15303-15319","acknowledgement":"AN, MF, and FL partially worked on ASIF when they were at Amazon Web Services in Tübingen,\r\nGermany. This paper is financially supported by the PRIN 2020 project no.2020TA3K9N (LEGO.AI), PNRR MUR project PE0000013-FAIR, and ERC Grant no.802554 (SPECGEO).","date_published":"2023-10-04T00:00:00Z","arxiv":1,"month":"10","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","type":"conference","publication_status":"published","alternative_title":["Advances in Neural Information Processing Systems"],"related_material":{"link":[{"url":"https://github.com/noranta4/ASIF","relation":"software"}]},"publication_identifier":{"isbn":["9781713899921"]},"_id":"14216","intvolume":"        36","OA_type":"green","article_processing_charge":"No","has_accepted_license":"1","quality_controlled":"1","file_date_updated":"2025-02-04T12:16:13Z","corr_author":"1"},{"external_id":{"arxiv":["2209.15430"]},"conference":{"end_date":"2023-05-05","name":"International Conference on Machine Learning Representations","start_date":"2023-05-01","location":"Kigali, Rwanda"},"publication":"The 11th International Conference on Learning Representations","quality_controlled":"1","extern":"1","article_processing_charge":"No","year":"2023","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","date_published":"2023-05-01T00:00:00Z","arxiv":1,"month":"05","publication_status":"published","oa_version":"Preprint","type":"conference","date_updated":"2023-09-13T09:44:26Z","title":"Relative representations enable zero-shot latent space communication","status":"public","day":"01","date_created":"2023-08-22T14:22:20Z","_id":"14217","main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/2209.15430"}],"citation":{"chicago":"Moschella, Luca, Valentino Maiorca, Marco Fumero, Antonio Norelli, Francesco Locatello, and Emanuele Rodolà. “Relative Representations Enable Zero-Shot Latent Space Communication.” In <i>The 11th International Conference on Learning Representations</i>, 2023.","ama":"Moschella L, Maiorca V, Fumero M, Norelli A, Locatello F, Rodolà E. Relative representations enable zero-shot latent space communication. In: <i>The 11th International Conference on Learning Representations</i>. ; 2023.","short":"L. Moschella, V. Maiorca, M. Fumero, A. Norelli, F. Locatello, E. Rodolà, in:, The 11th International Conference on Learning Representations, 2023.","mla":"Moschella, Luca, et al. “Relative Representations Enable Zero-Shot Latent Space Communication.” <i>The 11th International Conference on Learning Representations</i>, 2023.","ista":"Moschella L, Maiorca V, Fumero M, Norelli A, Locatello F, Rodolà E. 2023. Relative representations enable zero-shot latent space communication. The 11th International Conference on Learning Representations. International Conference on Machine Learning Representations.","apa":"Moschella, L., Maiorca, V., Fumero, M., Norelli, A., Locatello, F., &#38; Rodolà, E. (2023). Relative representations enable zero-shot latent space communication. In <i>The 11th International Conference on Learning Representations</i>. Kigali, Rwanda.","ieee":"L. Moschella, V. Maiorca, M. Fumero, A. Norelli, F. Locatello, and E. Rodolà, “Relative representations enable zero-shot latent space communication,” in <i>The 11th International Conference on Learning Representations</i>, Kigali, Rwanda, 2023."},"author":[{"full_name":"Moschella, Luca","first_name":"Luca","last_name":"Moschella"},{"last_name":"Maiorca","first_name":"Valentino","full_name":"Maiorca, Valentino"},{"last_name":"Fumero","first_name":"Marco","full_name":"Fumero, Marco"},{"first_name":"Antonio","last_name":"Norelli","full_name":"Norelli, Antonio"},{"first_name":"Francesco","last_name":"Locatello","full_name":"Locatello, Francesco","orcid":"0000-0002-4850-0683","id":"26cfd52f-2483-11ee-8040-88983bcc06d4"},{"full_name":"Rodolà, Emanuele","first_name":"Emanuele","last_name":"Rodolà"}],"abstract":[{"text":"Neural networks embed the geometric structure of a data manifold lying in a high-dimensional space into latent representations. Ideally, the distribution of the data points in the latent space should depend only on the task, the data, the loss, and other architecture-specific constraints. However, factors such as the random weights initialization, training hyperparameters, or other sources of randomness in the training phase may induce incoherent latent spaces that hinder any form of reuse. Nevertheless, we empirically observe that, under the same data and modeling choices, the angles between the encodings within distinct latent spaces do not change. In this work, we propose the latent similarity between each sample and a fixed set of anchors as an alternative data representation, demonstrating that it can enforce the desired invariances without any additional training. We show how neural architectures can leverage these relative representations to guarantee, in practice, invariance to latent isometries and rescalings, effectively enabling latent space communication: from zero-shot model stitching to latent space comparison between diverse settings. We extensively validate the generalization capability of our approach on different datasets, spanning various modalities (images, text, graphs), tasks (e.g., classification, reconstruction) and architectures (e.g., CNNs, GCNs, transformers).","lang":"eng"}],"department":[{"_id":"FrLo"}],"language":[{"iso":"eng"}],"oa":1},{"date_created":"2023-08-22T14:22:41Z","day":"10","author":[{"last_name":"Seitzer","first_name":"Maximilian","full_name":"Seitzer, Maximilian"},{"last_name":"Horn","first_name":"Max","full_name":"Horn, Max"},{"full_name":"Zadaianchuk, Andrii","last_name":"Zadaianchuk","first_name":"Andrii"},{"full_name":"Zietlow, Dominik","last_name":"Zietlow","first_name":"Dominik"},{"last_name":"Xiao","first_name":"Tianjun","full_name":"Xiao, Tianjun"},{"full_name":"Carl-Johann Simon-Gabriel, Carl-Johann Simon-Gabriel","first_name":"Carl-Johann Simon-Gabriel","last_name":"Carl-Johann Simon-Gabriel"},{"full_name":"He, Tong","last_name":"He","first_name":"Tong"},{"full_name":"Zhang, Zheng","first_name":"Zheng","last_name":"Zhang"},{"full_name":"Schölkopf, Bernhard","last_name":"Schölkopf","first_name":"Bernhard"},{"first_name":"Thomas","last_name":"Brox","full_name":"Brox, Thomas"},{"full_name":"Locatello, Francesco","orcid":"0000-0002-4850-0683","id":"26cfd52f-2483-11ee-8040-88983bcc06d4","last_name":"Locatello","first_name":"Francesco"}],"citation":{"short":"M. Seitzer, M. Horn, A. Zadaianchuk, D. Zietlow, T. Xiao, C.-J.S.-G. Carl-Johann Simon-Gabriel, T. He, Z. Zhang, B. Schölkopf, T. Brox, F. Locatello, in:, The 11th International Conference on Learning Representations, 2023.","ama":"Seitzer M, Horn M, Zadaianchuk A, et al. Bridging the gap to real-world object-centric learning. In: <i>The 11th International Conference on Learning Representations</i>. ; 2023.","chicago":"Seitzer, Maximilian, Max Horn, Andrii Zadaianchuk, Dominik Zietlow, Tianjun Xiao, Carl-Johann Simon-Gabriel Carl-Johann Simon-Gabriel, Tong He, et al. “Bridging the Gap to Real-World Object-Centric Learning.” In <i>The 11th International Conference on Learning Representations</i>, 2023.","mla":"Seitzer, Maximilian, et al. “Bridging the Gap to Real-World Object-Centric Learning.” <i>The 11th International Conference on Learning Representations</i>, 2023.","ista":"Seitzer M, Horn M, Zadaianchuk A, Zietlow D, Xiao T, Carl-Johann Simon-Gabriel C-JS-G, He T, Zhang Z, Schölkopf B, Brox T, Locatello F. 2023. Bridging the gap to real-world object-centric learning. The 11th International Conference on Learning Representations. ICLR: International Conference on Learning Representations.","ieee":"M. Seitzer <i>et al.</i>, “Bridging the gap to real-world object-centric learning,” in <i>The 11th International Conference on Learning Representations</i>, Kigali, Rwanda, 2023.","apa":"Seitzer, M., Horn, M., Zadaianchuk, A., Zietlow, D., Xiao, T., Carl-Johann Simon-Gabriel, C.-J. S.-G., … Locatello, F. (2023). Bridging the gap to real-world object-centric learning. In <i>The 11th International Conference on Learning Representations</i>. Kigali, Rwanda."},"main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/2209.14860"}],"_id":"14218","language":[{"iso":"eng"}],"department":[{"_id":"FrLo"}],"abstract":[{"lang":"eng","text":"Humans naturally decompose their environment into entities at the appropriate level of abstraction to act in the world. Allowing machine learning algorithms to derive this decomposition in an unsupervised way has become an important line of research. However, current methods are restricted to simulated data or require additional information in the form of motion or depth in order to successfully discover objects. In this work, we overcome this limitation by showing that reconstructing features from models trained in a self-supervised manner is a sufficient training signal for object-centric representations to arise in a fully unsupervised way. Our approach, DINOSAUR, significantly out-performs existing image-based object-centric learning models on simulated data and is the first unsupervised object-centric model that scales to real-world datasets such as COCO and PASCAL VOC. DINOSAUR is conceptually simple and shows competitive performance compared to more involved pipelines from the computer vision literature."}],"oa":1,"publication_status":"published","oa_version":"Preprint","date_updated":"2024-10-14T12:30:54Z","type":"conference","status":"public","title":"Bridging the gap to real-world object-centric learning","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","date_published":"2023-05-10T00:00:00Z","month":"05","arxiv":1,"conference":{"location":"Kigali, Rwanda","start_date":"2023-05-01","name":"ICLR: International Conference on Learning Representations","end_date":"2023-05-05"},"external_id":{"arxiv":["2209.14860"]},"quality_controlled":"1","publication":"The 11th International Conference on Learning Representations","year":"2023","extern":"1","article_processing_charge":"No"},{"publication_status":"published","oa_version":"Preprint","title":"Unsupervised semantic segmentation with self-supervised object-centric representations","status":"public","date_updated":"2023-09-13T11:25:43Z","type":"conference","main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/2207.05027"}],"_id":"14219","author":[{"full_name":"Zadaianchuk, Andrii","first_name":"Andrii","last_name":"Zadaianchuk"},{"last_name":"Kleindessner","first_name":"Matthaeus","full_name":"Kleindessner, Matthaeus"},{"first_name":"Yi","last_name":"Zhu","full_name":"Zhu, Yi"},{"full_name":"Locatello, Francesco","orcid":"0000-0002-4850-0683","id":"26cfd52f-2483-11ee-8040-88983bcc06d4","first_name":"Francesco","last_name":"Locatello"},{"full_name":"Brox, Thomas","last_name":"Brox","first_name":"Thomas"}],"citation":{"short":"A. Zadaianchuk, M. Kleindessner, Y. Zhu, F. Locatello, T. Brox, in:, The 11th International Conference on Learning Representations, 2023.","chicago":"Zadaianchuk, Andrii, Matthaeus Kleindessner, Yi Zhu, Francesco Locatello, and Thomas Brox. “Unsupervised Semantic Segmentation with Self-Supervised Object-Centric Representations.” In <i>The 11th International Conference on Learning Representations</i>, 2023.","ama":"Zadaianchuk A, Kleindessner M, Zhu Y, Locatello F, Brox T. Unsupervised semantic segmentation with self-supervised object-centric representations. In: <i>The 11th International Conference on Learning Representations</i>. ; 2023.","ista":"Zadaianchuk A, Kleindessner M, Zhu Y, Locatello F, Brox T. 2023. Unsupervised semantic segmentation with self-supervised object-centric representations. The 11th International Conference on Learning Representations. ICLR: International Conference on Learning Representations.","mla":"Zadaianchuk, Andrii, et al. “Unsupervised Semantic Segmentation with Self-Supervised Object-Centric Representations.” <i>The 11th International Conference on Learning Representations</i>, 2023.","ieee":"A. Zadaianchuk, M. Kleindessner, Y. Zhu, F. Locatello, and T. Brox, “Unsupervised semantic segmentation with self-supervised object-centric representations,” in <i>The 11th International Conference on Learning Representations</i>, Kigali, Rwanda, 2023.","apa":"Zadaianchuk, A., Kleindessner, M., Zhu, Y., Locatello, F., &#38; Brox, T. (2023). Unsupervised semantic segmentation with self-supervised object-centric representations. In <i>The 11th International Conference on Learning Representations</i>. Kigali, Rwanda."},"day":"01","date_created":"2023-08-22T14:22:58Z","oa":1,"abstract":[{"text":"In this paper, we show that recent advances in self-supervised feature\r\nlearning enable unsupervised object discovery and semantic segmentation with a\r\nperformance that matches the state of the field on supervised semantic\r\nsegmentation 10 years ago. We propose a methodology based on unsupervised\r\nsaliency masks and self-supervised feature clustering to kickstart object\r\ndiscovery followed by training a semantic segmentation network on pseudo-labels\r\nto bootstrap the system on images with multiple objects. We present results on\r\nPASCAL VOC that go far beyond the current state of the art (50.0 mIoU), and we\r\nreport for the first time results on MS COCO for the whole set of 81 classes:\r\nour method discovers 34 categories with more than $20\\%$ IoU, while obtaining\r\nan average IoU of 19.6 for all 81 categories.","lang":"eng"}],"language":[{"iso":"eng"}],"department":[{"_id":"FrLo"}],"publication":"The 11th International Conference on Learning Representations","quality_controlled":"1","external_id":{"arxiv":["2207.05027"]},"conference":{"location":"Kigali, Rwanda","name":"ICLR: International Conference on Learning Representations","start_date":"2023-05-01","end_date":"2023-05-05"},"extern":"1","article_processing_charge":"No","year":"2023","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","arxiv":1,"date_published":"2023-05-01T00:00:00Z","month":"05"},{"date_published":"2023-04-15T00:00:00Z","arxiv":1,"month":"04","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","year":"2023","extern":"1","article_processing_charge":"No","conference":{"end_date":"2023-04-14","start_date":"2023-04-11","name":"CLeaR: Conference on Causal Learning and Reasoning","location":"Tübingen, Germany"},"external_id":{"arxiv":["2110.06562"]},"quality_controlled":"1","publication":"2nd Conference on Causal Learning and Reasoning","language":[{"iso":"eng"}],"department":[{"_id":"FrLo"}],"abstract":[{"text":"Learning generative object models from unlabelled videos is a long standing problem and required for causal scene modeling. We decompose this problem into three easier subtasks, and provide candidate solutions for each of them. Inspired by the Common Fate Principle of Gestalt Psychology, we first extract (noisy) masks of moving objects via unsupervised motion segmentation. Second, generative models are trained on the masks of the background and the moving objects, respectively. Third, background and foreground models are combined in a conditional \"dead leaves\" scene model to sample novel scene configurations where occlusions and depth layering arise naturally. To evaluate the individual stages, we introduce the Fishbowl dataset positioned between complex real-world scenes and common object-centric benchmarks of simplistic objects. We show that our approach allows learning generative models that generalize beyond the occlusions present in the input videos, and represent scenes in a modular fashion that allows sampling plausible scenes outside the training distribution by permitting, for instance, object numbers or densities not observed in the training set.","lang":"eng"}],"oa":1,"date_created":"2023-08-22T14:23:54Z","day":"15","article_number":"2110.06562","citation":{"mla":"Tangemann, Matthias, et al. “Unsupervised Object Learning via Common Fate.” <i>2nd Conference on Causal Learning and Reasoning</i>, 2110.06562, 2023.","ista":"Tangemann M, Schneider S, Kügelgen J von, Locatello F, Gehler P, Brox T, Kümmerer M, Bethge M, Schölkopf B. 2023. Unsupervised object learning via common fate. 2nd Conference on Causal Learning and Reasoning. CLeaR: Conference on Causal Learning and Reasoning, 2110.06562.","short":"M. Tangemann, S. Schneider, J. von Kügelgen, F. Locatello, P. Gehler, T. Brox, M. Kümmerer, M. Bethge, B. Schölkopf, in:, 2nd Conference on Causal Learning and Reasoning, 2023.","ama":"Tangemann M, Schneider S, Kügelgen J von, et al. Unsupervised object learning via common fate. In: <i>2nd Conference on Causal Learning and Reasoning</i>. ; 2023.","chicago":"Tangemann, Matthias, Steffen Schneider, Julius von Kügelgen, Francesco Locatello, Peter Gehler, Thomas Brox, Matthias Kümmerer, Matthias Bethge, and Bernhard Schölkopf. “Unsupervised Object Learning via Common Fate.” In <i>2nd Conference on Causal Learning and Reasoning</i>, 2023.","ieee":"M. Tangemann <i>et al.</i>, “Unsupervised object learning via common fate,” in <i>2nd Conference on Causal Learning and Reasoning</i>, Tübingen, Germany, 2023.","apa":"Tangemann, M., Schneider, S., Kügelgen, J. von, Locatello, F., Gehler, P., Brox, T., … Schölkopf, B. (2023). Unsupervised object learning via common fate. In <i>2nd Conference on Causal Learning and Reasoning</i>. Tübingen, Germany."},"author":[{"full_name":"Tangemann, Matthias","first_name":"Matthias","last_name":"Tangemann"},{"full_name":"Schneider, Steffen","last_name":"Schneider","first_name":"Steffen"},{"first_name":"Julius von","last_name":"Kügelgen","full_name":"Kügelgen, Julius von"},{"full_name":"Locatello, Francesco","id":"26cfd52f-2483-11ee-8040-88983bcc06d4","orcid":"0000-0002-4850-0683","last_name":"Locatello","first_name":"Francesco"},{"full_name":"Gehler, Peter","first_name":"Peter","last_name":"Gehler"},{"full_name":"Brox, Thomas","first_name":"Thomas","last_name":"Brox"},{"full_name":"Kümmerer, Matthias","last_name":"Kümmerer","first_name":"Matthias"},{"first_name":"Matthias","last_name":"Bethge","full_name":"Bethge, Matthias"},{"full_name":"Schölkopf, Bernhard","last_name":"Schölkopf","first_name":"Bernhard"}],"_id":"14222","main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/2110.06562"}],"type":"conference","date_updated":"2023-09-13T11:31:14Z","title":"Unsupervised object learning via common fate","status":"public","publication_status":"published","oa_version":"Preprint"},{"oa":1,"abstract":[{"text":"We demonstrate that a sodium dimer, Na2(13Σ+u), residing on the surface of a helium nanodroplet, can be set into rotation by a nonresonant 1.0 ps infrared laser pulse. The time-dependent degree of alignment measured, exhibits a periodic, gradually decreasing structure that deviates qualitatively from that expected for gas-phase dimers. Comparison to alignment dynamics calculated from the time-dependent rotational Schrödinger equation shows that the deviation is due to the alignment dependent interaction between the dimer and the droplet surface. This interaction confines the dimer to the tangential plane of the droplet surface at the point where it resides and is the reason that the observed alignment dynamics is also well described by a 2D quantum rotor model.","lang":"eng"}],"department":[{"_id":"MiLe"}],"language":[{"iso":"eng"}],"main_file_link":[{"url":"https://doi.org/10.48550/arXiv.2308.15247","open_access":"1"}],"citation":{"ieee":"L. Kranabetter <i>et al.</i>, “Nonadiabatic laser-induced alignment dynamics of molecules on a surface,” <i>Physical Review Letters</i>, vol. 131, no. 5. American Physical Society, 2023.","apa":"Kranabetter, L., Kristensen, H. H., Ghazaryan, A., Schouder, C. A., Chatterley, A. S., Janssen, P., … Stapelfeldt, H. (2023). Nonadiabatic laser-induced alignment dynamics of molecules on a surface. <i>Physical Review Letters</i>. American Physical Society. <a href=\"https://doi.org/10.1103/PhysRevLett.131.053201\">https://doi.org/10.1103/PhysRevLett.131.053201</a>","ista":"Kranabetter L, Kristensen HH, Ghazaryan A, Schouder CA, Chatterley AS, Janssen P, Jensen F, Zillich RE, Lemeshko M, Stapelfeldt H. 2023. Nonadiabatic laser-induced alignment dynamics of molecules on a surface. Physical Review Letters. 131(5), 053201.","mla":"Kranabetter, Lorenz, et al. “Nonadiabatic Laser-Induced Alignment Dynamics of Molecules on a Surface.” <i>Physical Review Letters</i>, vol. 131, no. 5, 053201, American Physical Society, 2023, doi:<a href=\"https://doi.org/10.1103/PhysRevLett.131.053201\">10.1103/PhysRevLett.131.053201</a>.","chicago":"Kranabetter, Lorenz, Henrik H. Kristensen, Areg Ghazaryan, Constant A. Schouder, Adam S. Chatterley, Paul Janssen, Frank Jensen, Robert E. Zillich, Mikhail Lemeshko, and Henrik Stapelfeldt. “Nonadiabatic Laser-Induced Alignment Dynamics of Molecules on a Surface.” <i>Physical Review Letters</i>. American Physical Society, 2023. <a href=\"https://doi.org/10.1103/PhysRevLett.131.053201\">https://doi.org/10.1103/PhysRevLett.131.053201</a>.","ama":"Kranabetter L, Kristensen HH, Ghazaryan A, et al. Nonadiabatic laser-induced alignment dynamics of molecules on a surface. <i>Physical Review Letters</i>. 2023;131(5). doi:<a href=\"https://doi.org/10.1103/PhysRevLett.131.053201\">10.1103/PhysRevLett.131.053201</a>","short":"L. Kranabetter, H.H. Kristensen, A. Ghazaryan, C.A. Schouder, A.S. Chatterley, P. Janssen, F. Jensen, R.E. Zillich, M. Lemeshko, H. Stapelfeldt, Physical Review Letters 131 (2023)."},"publisher":"American Physical Society","author":[{"full_name":"Kranabetter, Lorenz","first_name":"Lorenz","last_name":"Kranabetter"},{"full_name":"Kristensen, Henrik H.","first_name":"Henrik H.","last_name":"Kristensen"},{"full_name":"Ghazaryan, Areg","orcid":"0000-0001-9666-3543","id":"4AF46FD6-F248-11E8-B48F-1D18A9856A87","first_name":"Areg","last_name":"Ghazaryan"},{"last_name":"Schouder","first_name":"Constant A.","full_name":"Schouder, Constant A."},{"full_name":"Chatterley, Adam S.","first_name":"Adam S.","last_name":"Chatterley"},{"full_name":"Janssen, Paul","last_name":"Janssen","first_name":"Paul"},{"full_name":"Jensen, Frank","first_name":"Frank","last_name":"Jensen"},{"first_name":"Robert E.","last_name":"Zillich","full_name":"Zillich, Robert E."},{"full_name":"Lemeshko, Mikhail","orcid":"0000-0002-6990-7802","id":"37CB05FA-F248-11E8-B48F-1D18A9856A87","first_name":"Mikhail","last_name":"Lemeshko"},{"first_name":"Henrik","last_name":"Stapelfeldt","full_name":"Stapelfeldt, Henrik"}],"day":"04","date_created":"2023-08-27T22:01:16Z","title":"Nonadiabatic laser-induced alignment dynamics of molecules on a surface","status":"public","volume":131,"date_updated":"2025-04-14T07:48:54Z","oa_version":"Preprint","scopus_import":"1","acknowledgement":"H. S. acknowledges support from The Villum Foundation through a Villum Investigator Grant No. 25886. M. L. acknowledges support by the European Research Council (ERC) Starting Grant No. 801770 (ANGULON). F. J. and R. E. Z. acknowledge support from the Centre for Scientific Computing, Aarhus and the JKU scientific computing administration, Linz, respectively.","arxiv":1,"month":"08","date_published":"2023-08-04T00:00:00Z","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","year":"2023","ec_funded":1,"publication":"Physical Review Letters","project":[{"call_identifier":"H2020","name":"Angulon: physics and applications of a new quasiparticle","grant_number":"801770","_id":"2688CF98-B435-11E9-9278-68D0E5697425"}],"external_id":{"isi":["001101784100001"],"pmid":["37595218"],"arxiv":["2308.15247"]},"publication_identifier":{"issn":["0031-9007"],"eissn":["1079-7114"]},"pmid":1,"_id":"14238","issue":"5","intvolume":"       131","article_number":"053201","doi":"10.1103/PhysRevLett.131.053201","type":"journal_article","publication_status":"published","article_type":"original","fulldoi":"https://doi.org/10.1103/PhysRevLett.131.053201","isi":1,"article_processing_charge":"No","quality_controlled":"1"},{"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","month":"08","date_published":"2023-08-03T00:00:00Z","arxiv":1,"scopus_import":"1","acknowledgement":"We thank Agnieszka Bodzenta-Skibińska, Paolo Cascini, Wahei Hara, Sándor Kovács, Alexander Kuznetsov, Mircea Musta  ă, Nebojsa Pavic, Pavel Sechin, and Michael Wemyss for discussions and e-mail correspondence. We also thank the anonymous referee for the helpful comments. M.M. was supported by the Institute of Science and Technology Austria. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement no. 101034413. E.S. was partially supported by the EPSRC grant EP/T019379/1 “Derived categories and algebraic K-theory of singularities”, and by the ERC Synergy grant “Modern Aspects of Geometry: Categories, Cycles and Cohomology of Hyperkähler Varieties.”\r\n\r\n","file":[{"relation":"main_file","content_type":"application/pdf","file_name":"2023_ForumMathematics_Mauri.pdf","creator":"dernst","file_id":"14266","file_size":280865,"date_updated":"2023-09-05T06:43:11Z","checksum":"c36241750cc5cb06890aec0ecdfee626","access_level":"open_access","success":1,"date_created":"2023-09-05T06:43:11Z"}],"publication":"Forum of Mathematics, Sigma","external_id":{"arxiv":["2212.06786"],"isi":["001041926700001"]},"project":[{"name":"IST-BRIDGE: International postdoctoral program","call_identifier":"H2020","grant_number":"101034413","_id":"fc2ed2f7-9c52-11eb-aca3-c01059dda49c"}],"year":"2023","ec_funded":1,"citation":{"ieee":"M. Mauri and E. Shinder, “Homological Bondal-Orlov localization conjecture for rational singularities,” <i>Forum of Mathematics, Sigma</i>, vol. 11. Cambridge University Press, 2023.","apa":"Mauri, M., &#38; Shinder, E. (2023). Homological Bondal-Orlov localization conjecture for rational singularities. <i>Forum of Mathematics, Sigma</i>. Cambridge University Press. <a href=\"https://doi.org/10.1017/fms.2023.65\">https://doi.org/10.1017/fms.2023.65</a>","mla":"Mauri, Mirko, and Evgeny Shinder. “Homological Bondal-Orlov Localization Conjecture for Rational Singularities.” <i>Forum of Mathematics, Sigma</i>, vol. 11, e66, Cambridge University Press, 2023, doi:<a href=\"https://doi.org/10.1017/fms.2023.65\">10.1017/fms.2023.65</a>.","ista":"Mauri M, Shinder E. 2023. Homological Bondal-Orlov localization conjecture for rational singularities. Forum of Mathematics, Sigma. 11, e66.","ama":"Mauri M, Shinder E. Homological Bondal-Orlov localization conjecture for rational singularities. <i>Forum of Mathematics, Sigma</i>. 2023;11. doi:<a href=\"https://doi.org/10.1017/fms.2023.65\">10.1017/fms.2023.65</a>","short":"M. Mauri, E. Shinder, Forum of Mathematics, Sigma 11 (2023).","chicago":"Mauri, Mirko, and Evgeny Shinder. “Homological Bondal-Orlov Localization Conjecture for Rational Singularities.” <i>Forum of Mathematics, Sigma</i>. Cambridge University Press, 2023. <a href=\"https://doi.org/10.1017/fms.2023.65\">https://doi.org/10.1017/fms.2023.65</a>."},"author":[{"first_name":"Mirko","last_name":"Mauri","full_name":"Mauri, Mirko","id":"2cf70c34-09c1-11ed-bd8d-c34fac206130"},{"last_name":"Shinder","first_name":"Evgeny","full_name":"Shinder, Evgeny"}],"publisher":"Cambridge University Press","date_created":"2023-08-27T22:01:16Z","day":"03","oa":1,"department":[{"_id":"TaHa"}],"language":[{"iso":"eng"}],"abstract":[{"text":"Given a resolution of rational singularities  π:X~→X  over a field of characteristic zero, we use a Hodge-theoretic argument to prove that the image of the functor  Rπ∗:Db(X~)→Db(X)\r\n  between bounded derived categories of coherent sheaves generates  Db(X)\r\n  as a triangulated category. This gives a weak version of the Bondal–Orlov localization conjecture [BO02], answering a question from [PS21]. The same result is established more generally for proper (not necessarily birational) morphisms  π:X~→X , with  X~\r\n  smooth, satisfying  Rπ∗(OX~)=OX .","lang":"eng"}],"oa_version":"Published Version","ddc":["510"],"title":"Homological Bondal-Orlov localization conjecture for rational singularities","tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","image":"/images/cc_by.png","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)"},"status":"public","date_updated":"2025-04-14T07:54:52Z","volume":11,"isi":1,"corr_author":"1","fulldoi":"https://doi.org/10.1017/fms.2023.65","article_type":"original","quality_controlled":"1","has_accepted_license":"1","file_date_updated":"2023-09-05T06:43:11Z","article_processing_charge":"Yes","_id":"14239","intvolume":"        11","article_number":"e66","publication_identifier":{"eissn":["2050-5094"]},"publication_status":"published","doi":"10.1017/fms.2023.65","type":"journal_article"},{"year":"2023","file":[{"checksum":"1d178bb2f8011d9f5aedda6427e18c7a","date_created":"2023-12-21T12:26:40Z","success":1,"access_level":"open_access","creator":"sjeschke","file_id":"14704","date_updated":"2023-12-21T12:26:40Z","file_size":511572575,"content_type":"video/mp4","relation":"main_file","file_name":"PaperVideo_final.mp4"},{"access_level":"open_access","date_created":"2024-01-02T09:34:27Z","success":1,"checksum":"a49b2e744d5cd1276bb8b2e0ce6dc638","file_name":"2023_ACMToG_Jeschke.pdf","relation":"main_file","content_type":"application/pdf","file_size":7469177,"date_updated":"2024-01-02T09:34:27Z","creator":"dernst","file_id":"14725"}],"publication":"ACM Transactions on Graphics","external_id":{"isi":["001044671300049"]},"project":[{"_id":"34bc2376-11ca-11ed-8bc3-9a3b3961a088","grant_number":"101045083","name":"Computational Discovery of Numerical Algorithms for Animation and Simulation of Natural Phenomena"}],"date_published":"2023-08-01T00:00:00Z","month":"08","acknowledgement":"We thank Georg Sperl for helping with early research for this paper, Mickael Ly and Yi-Lu Chen for proofreading, and members of the ISTA Visual Computing Group for general feedback. This project was funded in part by the European Research Council (ERC Consolidator Grant 101045083 CoDiNA).\r\nThe motorboat and sailboat were modeled by Sergei and the palmtrees by YadroGames. The environment map was created by Emil Persson.","scopus_import":"1","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","title":"Generalizing shallow water simulations with dispersive surface waves","tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","image":"/images/cc_by.png","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)"},"status":"public","volume":42,"date_updated":"2025-04-14T08:01:13Z","oa_version":"Published Version","acknowledged_ssus":[{"_id":"ScienComp"}],"ddc":["000"],"oa":1,"department":[{"_id":"ChWo"}],"language":[{"iso":"eng"}],"abstract":[{"lang":"eng","text":"This paper introduces a novel method for simulating large bodies of water as a height field. At the start of each time step, we partition the waves into a bulk flow (which approximately satisfies the assumptions of the shallow water equations) and surface waves (which approximately satisfy the assumptions of Airy wave theory). We then solve the two wave regimes separately using appropriate state-of-the-art techniques, and re-combine the resulting wave velocities at the end of each step. This strategy leads to the first heightfield wave model capable of simulating complex interactions between both deep and shallow water effects, like the waves from a boat wake sloshing up onto a beach, or a dam break producing wave interference patterns and eddies. We also analyze the numerical dispersion created by our method and derive an exact correction factor for waves at a constant water depth, giving us a numerically perfect re-creation of theoretical water wave dispersion patterns."}],"publisher":"Association for Computing Machinery","author":[{"first_name":"Stefan","last_name":"Jeschke","id":"44D6411A-F248-11E8-B48F-1D18A9856A87","full_name":"Jeschke, Stefan"},{"first_name":"Christopher J","last_name":"Wojtan","full_name":"Wojtan, Christopher J","id":"3C61F1D2-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-6646-5546"}],"citation":{"ista":"Jeschke S, Wojtan C. 2023. Generalizing shallow water simulations with dispersive surface waves. ACM Transactions on Graphics. 42(4), 83.","mla":"Jeschke, Stefan, and Chris Wojtan. “Generalizing Shallow Water Simulations with Dispersive Surface Waves.” <i>ACM Transactions on Graphics</i>, vol. 42, no. 4, 83, Association for Computing Machinery, 2023, doi:<a href=\"https://doi.org/10.1145/3592098\">10.1145/3592098</a>.","short":"S. Jeschke, C. Wojtan, ACM Transactions on Graphics 42 (2023).","chicago":"Jeschke, Stefan, and Chris Wojtan. “Generalizing Shallow Water Simulations with Dispersive Surface Waves.” <i>ACM Transactions on Graphics</i>. Association for Computing Machinery, 2023. <a href=\"https://doi.org/10.1145/3592098\">https://doi.org/10.1145/3592098</a>.","ama":"Jeschke S, Wojtan C. Generalizing shallow water simulations with dispersive surface waves. <i>ACM Transactions on Graphics</i>. 2023;42(4). doi:<a href=\"https://doi.org/10.1145/3592098\">10.1145/3592098</a>","ieee":"S. Jeschke and C. Wojtan, “Generalizing shallow water simulations with dispersive surface waves,” <i>ACM Transactions on Graphics</i>, vol. 42, no. 4. Association for Computing Machinery, 2023.","apa":"Jeschke, S., &#38; Wojtan, C. (2023). Generalizing shallow water simulations with dispersive surface waves. <i>ACM Transactions on Graphics</i>. Association for Computing Machinery. <a href=\"https://doi.org/10.1145/3592098\">https://doi.org/10.1145/3592098</a>"},"date_created":"2023-08-27T22:01:17Z","day":"01","article_processing_charge":"Yes (in subscription journal)","quality_controlled":"1","has_accepted_license":"1","file_date_updated":"2024-01-02T09:34:27Z","fulldoi":"https://doi.org/10.1145/3592098","article_type":"original","isi":1,"corr_author":"1","doi":"10.1145/3592098","type":"journal_article","publication_status":"published","publication_identifier":{"eissn":["1557-7368"],"issn":["0730-0301"]},"issue":"4","_id":"14240","article_number":"83","intvolume":"        42"},{"publication_status":"published","doi":"10.1145/3588432.3591542","type":"conference","_id":"14241","article_number":"20","publication_identifier":{"isbn":["9798400701597"]},"quality_controlled":"1","article_processing_charge":"No","corr_author":"1","isi":1,"fulldoi":"https://doi.org/10.1145/3588432.3591542","oa_version":"Preprint","title":"Stealth shaper: Reflectivity optimization as surface stylization","status":"public","date_updated":"2025-09-09T12:49:15Z","main_file_link":[{"open_access":"1","url":"https://doi.org/10.48550/arXiv.2305.05944"}],"citation":{"mla":"Tojo, Kenji, et al. “Stealth Shaper: Reflectivity Optimization as Surface Stylization.” <i>SIGGRAPH 2023 Conference Proceedings</i>, 20, Association for Computing Machinery, 2023, doi:<a href=\"https://doi.org/10.1145/3588432.3591542\">10.1145/3588432.3591542</a>.","ista":"Tojo K, Shamir A, Bickel B, Umetani N. 2023. Stealth shaper: Reflectivity optimization as surface stylization. SIGGRAPH 2023 Conference Proceedings. SIGGRAPH: Computer Graphics and Interactive Techniques Conference, 20.","ama":"Tojo K, Shamir A, Bickel B, Umetani N. Stealth shaper: Reflectivity optimization as surface stylization. In: <i>SIGGRAPH 2023 Conference Proceedings</i>. Association for Computing Machinery; 2023. doi:<a href=\"https://doi.org/10.1145/3588432.3591542\">10.1145/3588432.3591542</a>","short":"K. Tojo, A. Shamir, B. Bickel, N. Umetani, in:, SIGGRAPH 2023 Conference Proceedings, Association for Computing Machinery, 2023.","chicago":"Tojo, Kenji, Ariel Shamir, Bernd Bickel, and Nobuyuki Umetani. “Stealth Shaper: Reflectivity Optimization as Surface Stylization.” In <i>SIGGRAPH 2023 Conference Proceedings</i>. Association for Computing Machinery, 2023. <a href=\"https://doi.org/10.1145/3588432.3591542\">https://doi.org/10.1145/3588432.3591542</a>.","apa":"Tojo, K., Shamir, A., Bickel, B., &#38; Umetani, N. (2023). Stealth shaper: Reflectivity optimization as surface stylization. In <i>SIGGRAPH 2023 Conference Proceedings</i>. Los Angeles, CA, United States: Association for Computing Machinery. <a href=\"https://doi.org/10.1145/3588432.3591542\">https://doi.org/10.1145/3588432.3591542</a>","ieee":"K. Tojo, A. Shamir, B. Bickel, and N. Umetani, “Stealth shaper: Reflectivity optimization as surface stylization,” in <i>SIGGRAPH 2023 Conference Proceedings</i>, Los Angeles, CA, United States, 2023."},"publisher":"Association for Computing Machinery","author":[{"full_name":"Tojo, Kenji","first_name":"Kenji","last_name":"Tojo"},{"last_name":"Shamir","first_name":"Ariel","full_name":"Shamir, Ariel"},{"last_name":"Bickel","first_name":"Bernd","orcid":"0000-0001-6511-9385","id":"49876194-F248-11E8-B48F-1D18A9856A87","full_name":"Bickel, Bernd"},{"first_name":"Nobuyuki","last_name":"Umetani","full_name":"Umetani, Nobuyuki"}],"day":"23","date_created":"2023-08-27T22:01:17Z","oa":1,"abstract":[{"text":"We present a technique to optimize the reflectivity of a surface while preserving its overall shape. The naïve optimization of the mesh vertices using the gradients of reflectivity simulations results in undesirable distortion. In contrast, our robust formulation optimizes the surface normal as an independent variable that bridges the reflectivity term with differential rendering, and the regularization term with as-rigid-as-possible elastic energy. We further adaptively subdivide the input mesh to improve the convergence. Consequently, our method can minimize the retroreflectivity of a wide range of input shapes, resulting in sharply creased shapes ubiquitous among stealth aircraft and Sci-Fi vehicles. Furthermore, by changing the reward for the direction of the outgoing light directions, our method can be applied to other reflectivity design tasks, such as the optimization of architectural walls to concentrate light in a specific region. We have tested the proposed method using light-transport simulations and real-world 3D-printed objects.","lang":"eng"}],"language":[{"iso":"eng"}],"department":[{"_id":"BeBi"}],"publication":"SIGGRAPH 2023 Conference Proceedings","external_id":{"arxiv":["2305.05944"],"isi":["001117690500020"]},"conference":{"end_date":"2023-08-10","name":"SIGGRAPH: Computer Graphics and Interactive Techniques Conference","start_date":"2023-08-06","location":"Los Angeles, CA, United States"},"year":"2023","user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","acknowledgement":"The authors would like to thank Yuki Koyama and Takeo Igarashi for early discussions, and Yuta Yaguchi for support in 3D printing. This research is partially supported by the Israel Science Foundation grant number 1390/19.\r\n","scopus_import":"1","month":"07","date_published":"2023-07-23T00:00:00Z","arxiv":1},{"year":"2023","ec_funded":1,"publication":"Proceedings of the 37th AAAI Conference on Artificial Intelligence","project":[{"grant_number":"101020093","_id":"62781420-2b32-11ec-9570-8d9b63373d4d","name":"Vigilant Algorithmic Monitoring of Software","call_identifier":"H2020"},{"_id":"0599E47C-7A3F-11EA-A408-12923DDC885E","grant_number":"863818","name":"Formal Methods for Stochastic Models: Algorithms and Applications","call_identifier":"H2020"},{"grant_number":"665385","_id":"2564DBCA-B435-11E9-9278-68D0E5697425","name":"International IST Doctoral Program","call_identifier":"H2020"}],"external_id":{"arxiv":["2211.16187"]},"conference":{"name":"AAAI: Conference on Artificial Intelligence","start_date":"2023-02-07","end_date":"2023-02-14","location":"Washington, DC, United States"},"page":"14964-14973","acknowledgement":"This work was supported in part by the ERC-2020-AdG 101020093, ERC CoG 863818 (FoRM-SMArt) and the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Grant Agreement No. 665385. Research was sponsored by the United\r\nStates Air Force Research Laboratory and the United States Air Force Artificial Intelligence Accelerator and was accomplished under Cooperative Agreement Number FA8750-19-2-\r\n1000. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied,\r\nof the United States Air Force or the U.S. Government. The U.S. Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright\r\nnotation herein. The research was also funded in part by the AI2050 program at Schmidt Futures (Grant G-22-63172) and Capgemini SE.","scopus_import":"1","month":"06","date_published":"2023-06-26T00:00:00Z","arxiv":1,"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","status":"public","title":"Quantization-aware interval bound propagation for training certifiably robust quantized neural networks","date_updated":"2025-03-31T16:01:08Z","volume":37,"oa_version":"Preprint","oa":1,"abstract":[{"lang":"eng","text":"We study the problem of training and certifying adversarially robust quantized neural networks (QNNs). Quantization is a technique for making neural networks more efficient by running them using low-bit integer arithmetic and is therefore commonly adopted in industry. Recent work has shown that floating-point neural networks that have been verified to be robust can become vulnerable to adversarial attacks after quantization, and certification of the quantized representation is necessary to guarantee robustness. In this work, we present quantization-aware interval bound propagation (QA-IBP), a novel method for training robust QNNs. Inspired by advances in robust learning of non-quantized networks, our training algorithm computes the gradient of an abstract representation of the actual network. Unlike existing approaches, our method can handle the discrete semantics of QNNs. Based on QA-IBP, we also develop a complete verification procedure for verifying the adversarial robustness of QNNs, which is guaranteed to terminate and produce a correct answer. Compared to existing approaches, the key advantage of our verification procedure is that it runs entirely on GPU or other accelerator devices. We demonstrate experimentally that our approach significantly outperforms existing methods and establish the new state-of-the-art for training and certifying the robustness of QNNs."}],"department":[{"_id":"ToHe"},{"_id":"KrCh"}],"language":[{"iso":"eng"}],"main_file_link":[{"open_access":"1","url":"https://doi.org/10.48550/arXiv.2211.16187"}],"publisher":"Association for the Advancement of Artificial Intelligence","author":[{"id":"3DC22916-F248-11E8-B48F-1D18A9856A87","full_name":"Lechner, Mathias","first_name":"Mathias","last_name":"Lechner"},{"last_name":"Zikelic","first_name":"Dorde","orcid":"0000-0002-4681-1699","id":"294AA7A6-F248-11E8-B48F-1D18A9856A87","full_name":"Zikelic, Dorde"},{"id":"2E5DCA20-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-4561-241X","full_name":"Chatterjee, Krishnendu","first_name":"Krishnendu","last_name":"Chatterjee"},{"orcid":"0000-0002-2985-7724","id":"40876CD8-F248-11E8-B48F-1D18A9856A87","full_name":"Henzinger, Thomas A","last_name":"Henzinger","first_name":"Thomas A"},{"full_name":"Rus, Daniela","first_name":"Daniela","last_name":"Rus"}],"citation":{"ista":"Lechner M, Zikelic D, Chatterjee K, Henzinger TA, Rus D. 2023. Quantization-aware interval bound propagation for training certifiably robust quantized neural networks. Proceedings of the 37th AAAI Conference on Artificial Intelligence. AAAI: Conference on Artificial Intelligence vol. 37, 14964–14973.","mla":"Lechner, Mathias, et al. “Quantization-Aware Interval Bound Propagation for Training Certifiably Robust Quantized Neural Networks.” <i>Proceedings of the 37th AAAI Conference on Artificial Intelligence</i>, vol. 37, no. 12, Association for the Advancement of Artificial Intelligence, 2023, pp. 14964–73, doi:<a href=\"https://doi.org/10.1609/aaai.v37i12.26747\">10.1609/aaai.v37i12.26747</a>.","chicago":"Lechner, Mathias, Dorde Zikelic, Krishnendu Chatterjee, Thomas A Henzinger, and Daniela Rus. “Quantization-Aware Interval Bound Propagation for Training Certifiably Robust Quantized Neural Networks.” In <i>Proceedings of the 37th AAAI Conference on Artificial Intelligence</i>, 37:14964–73. Association for the Advancement of Artificial Intelligence, 2023. <a href=\"https://doi.org/10.1609/aaai.v37i12.26747\">https://doi.org/10.1609/aaai.v37i12.26747</a>.","ama":"Lechner M, Zikelic D, Chatterjee K, Henzinger TA, Rus D. Quantization-aware interval bound propagation for training certifiably robust quantized neural networks. In: <i>Proceedings of the 37th AAAI Conference on Artificial Intelligence</i>. Vol 37. Association for the Advancement of Artificial Intelligence; 2023:14964-14973. doi:<a href=\"https://doi.org/10.1609/aaai.v37i12.26747\">10.1609/aaai.v37i12.26747</a>","short":"M. Lechner, D. Zikelic, K. Chatterjee, T.A. Henzinger, D. Rus, in:, Proceedings of the 37th AAAI Conference on Artificial Intelligence, Association for the Advancement of Artificial Intelligence, 2023, pp. 14964–14973.","apa":"Lechner, M., Zikelic, D., Chatterjee, K., Henzinger, T. A., &#38; Rus, D. (2023). Quantization-aware interval bound propagation for training certifiably robust quantized neural networks. In <i>Proceedings of the 37th AAAI Conference on Artificial Intelligence</i> (Vol. 37, pp. 14964–14973). Washington, DC, United States: Association for the Advancement of Artificial Intelligence. <a href=\"https://doi.org/10.1609/aaai.v37i12.26747\">https://doi.org/10.1609/aaai.v37i12.26747</a>","ieee":"M. Lechner, D. Zikelic, K. Chatterjee, T. A. Henzinger, and D. Rus, “Quantization-aware interval bound propagation for training certifiably robust quantized neural networks,” in <i>Proceedings of the 37th AAAI Conference on Artificial Intelligence</i>, Washington, DC, United States, 2023, vol. 37, no. 12, pp. 14964–14973."},"day":"26","date_created":"2023-08-27T22:01:17Z","article_processing_charge":"No","quality_controlled":"1","fulldoi":"https://doi.org/10.1609/aaai.v37i12.26747","doi":"10.1609/aaai.v37i12.26747","type":"conference","publication_status":"published","publication_identifier":{"isbn":["9781577358800"]},"_id":"14242","issue":"12","intvolume":"        37"}]