[{"extern":"1","scopus_import":"1","intvolume":"        21","oa":1,"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","issue":"21","main_file_link":[{"url":"https://doi.org/10.1021/acs.nanolett.1c02145","open_access":"1"}],"volume":21,"external_id":{"pmid":["34676752"],"arxiv":["2109.15291"]},"date_created":"2023-08-09T13:09:15Z","_id":"13996","page":"8970-8978","publication":"Nano Letters","article_processing_charge":"No","keyword":["Mechanical Engineering","Condensed Matter Physics","General Materials Science","General Chemistry","Bioengineering"],"date_published":"2021-10-22T00:00:00Z","month":"10","date_updated":"2023-08-22T07:32:00Z","title":"All-optical probe of three-dimensional topological insulators based on high-harmonic generation by circularly polarized laser fields","article_type":"original","citation":{"chicago":"Baykusheva, Denitsa Rangelova, Alexis Chacón, Jian Lu, Trevor P. Bailey, Jonathan A. Sobota, Hadas Soifer, Patrick S. Kirchmann, et al. “All-Optical Probe of Three-Dimensional Topological Insulators Based on High-Harmonic Generation by Circularly Polarized Laser Fields.” <i>Nano Letters</i>. American Chemical Society, 2021. <a href=\"https://doi.org/10.1021/acs.nanolett.1c02145\">https://doi.org/10.1021/acs.nanolett.1c02145</a>.","ama":"Baykusheva DR, Chacón A, Lu J, et al. All-optical probe of three-dimensional topological insulators based on high-harmonic generation by circularly polarized laser fields. <i>Nano Letters</i>. 2021;21(21):8970-8978. doi:<a href=\"https://doi.org/10.1021/acs.nanolett.1c02145\">10.1021/acs.nanolett.1c02145</a>","ista":"Baykusheva DR, Chacón A, Lu J, Bailey TP, Sobota JA, Soifer H, Kirchmann PS, Rotundu C, Uher C, Heinz TF, Reis DA, Ghimire S. 2021. All-optical probe of three-dimensional topological insulators based on high-harmonic generation by circularly polarized laser fields. Nano Letters. 21(21), 8970–8978.","mla":"Baykusheva, Denitsa Rangelova, et al. “All-Optical Probe of Three-Dimensional Topological Insulators Based on High-Harmonic Generation by Circularly Polarized Laser Fields.” <i>Nano Letters</i>, vol. 21, no. 21, American Chemical Society, 2021, pp. 8970–78, doi:<a href=\"https://doi.org/10.1021/acs.nanolett.1c02145\">10.1021/acs.nanolett.1c02145</a>.","apa":"Baykusheva, D. R., Chacón, A., Lu, J., Bailey, T. P., Sobota, J. A., Soifer, H., … Ghimire, S. (2021). All-optical probe of three-dimensional topological insulators based on high-harmonic generation by circularly polarized laser fields. <i>Nano Letters</i>. American Chemical Society. <a href=\"https://doi.org/10.1021/acs.nanolett.1c02145\">https://doi.org/10.1021/acs.nanolett.1c02145</a>","short":"D.R. Baykusheva, A. Chacón, J. Lu, T.P. Bailey, J.A. Sobota, H. Soifer, P.S. Kirchmann, C. Rotundu, C. Uher, T.F. Heinz, D.A. Reis, S. Ghimire, Nano Letters 21 (2021) 8970–8978.","ieee":"D. R. Baykusheva <i>et al.</i>, “All-optical probe of three-dimensional topological insulators based on high-harmonic generation by circularly polarized laser fields,” <i>Nano Letters</i>, vol. 21, no. 21. American Chemical Society, pp. 8970–8978, 2021."},"type":"journal_article","quality_controlled":"1","status":"public","pmid":1,"language":[{"iso":"eng"}],"abstract":[{"lang":"eng","text":"We report the observation of an anomalous nonlinear optical response of the prototypical three-dimensional topological insulator bismuth selenide through the process of high-order harmonic generation. We find that the generation efficiency increases as the laser polarization is changed from linear to elliptical, and it becomes maximum for circular polarization. With the aid of a microscopic theory and a detailed analysis of the measured spectra, we reveal that such anomalous enhancement encodes the characteristic topology of the band structure that originates from the interplay of strong spin–orbit coupling and time-reversal symmetry protection. The implications are in ultrafast probing of topological phase transitions, light-field driven dissipationless electronics, and quantum computation."}],"publication_status":"published","day":"22","publisher":"American Chemical Society","oa_version":"Published Version","arxiv":1,"doi":"10.1021/acs.nanolett.1c02145","year":"2021","author":[{"id":"71b4d059-2a03-11ee-914d-dfa3beed6530","first_name":"Denitsa Rangelova","last_name":"Baykusheva","full_name":"Baykusheva, Denitsa Rangelova"},{"last_name":"Chacón","full_name":"Chacón, Alexis","first_name":"Alexis"},{"full_name":"Lu, Jian","last_name":"Lu","first_name":"Jian"},{"full_name":"Bailey, Trevor P.","last_name":"Bailey","first_name":"Trevor P."},{"last_name":"Sobota","full_name":"Sobota, Jonathan A.","first_name":"Jonathan A."},{"first_name":"Hadas","last_name":"Soifer","full_name":"Soifer, Hadas"},{"full_name":"Kirchmann, Patrick S.","last_name":"Kirchmann","first_name":"Patrick S."},{"full_name":"Rotundu, Costel","last_name":"Rotundu","first_name":"Costel"},{"first_name":"Ctirad","last_name":"Uher","full_name":"Uher, Ctirad"},{"full_name":"Heinz, Tony F.","last_name":"Heinz","first_name":"Tony F."},{"first_name":"David A.","last_name":"Reis","full_name":"Reis, David A."},{"last_name":"Ghimire","full_name":"Ghimire, Shambhu","first_name":"Shambhu"}],"publication_identifier":{"issn":["1530-6984"],"eissn":["1530-6992"]}},{"external_id":{"arxiv":["2008.01265"]},"date_created":"2023-08-09T13:09:26Z","_id":"13997","publication":"Physical Review A","article_processing_charge":"No","date_published":"2021-02-01T00:00:00Z","month":"02","date_updated":"2023-08-22T07:33:43Z","title":"Strong-field physics in three-dimensional topological insulators","extern":"1","scopus_import":"1","intvolume":"       103","oa":1,"issue":"2","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","article_number":"023101","main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/2008.01265"}],"volume":103,"day":"01","publisher":"American Physical Society","arxiv":1,"oa_version":"Preprint","doi":"10.1103/physreva.103.023101","year":"2021","author":[{"full_name":"Baykusheva, Denitsa Rangelova","last_name":"Baykusheva","id":"71b4d059-2a03-11ee-914d-dfa3beed6530","first_name":"Denitsa Rangelova"},{"first_name":"Alexis","last_name":"Chacón","full_name":"Chacón, Alexis"},{"full_name":"Kim, Dasol","last_name":"Kim","first_name":"Dasol"},{"last_name":"Kim","full_name":"Kim, Dong Eon","first_name":"Dong Eon"},{"first_name":"David A.","full_name":"Reis, David A.","last_name":"Reis"},{"full_name":"Ghimire, Shambhu","last_name":"Ghimire","first_name":"Shambhu"}],"publication_identifier":{"issn":["2469-9926"],"eissn":["2469-9934"]},"article_type":"original","citation":{"short":"D.R. Baykusheva, A. Chacón, D. Kim, D.E. Kim, D.A. Reis, S. Ghimire, Physical Review A 103 (2021).","apa":"Baykusheva, D. R., Chacón, A., Kim, D., Kim, D. E., Reis, D. A., &#38; Ghimire, S. (2021). Strong-field physics in three-dimensional topological insulators. <i>Physical Review A</i>. American Physical Society. <a href=\"https://doi.org/10.1103/physreva.103.023101\">https://doi.org/10.1103/physreva.103.023101</a>","ieee":"D. R. Baykusheva, A. Chacón, D. Kim, D. E. Kim, D. A. Reis, and S. Ghimire, “Strong-field physics in three-dimensional topological insulators,” <i>Physical Review A</i>, vol. 103, no. 2. American Physical Society, 2021.","chicago":"Baykusheva, Denitsa Rangelova, Alexis Chacón, Dasol Kim, Dong Eon Kim, David A. Reis, and Shambhu Ghimire. “Strong-Field Physics in Three-Dimensional Topological Insulators.” <i>Physical Review A</i>. American Physical Society, 2021. <a href=\"https://doi.org/10.1103/physreva.103.023101\">https://doi.org/10.1103/physreva.103.023101</a>.","ama":"Baykusheva DR, Chacón A, Kim D, Kim DE, Reis DA, Ghimire S. Strong-field physics in three-dimensional topological insulators. <i>Physical Review A</i>. 2021;103(2). doi:<a href=\"https://doi.org/10.1103/physreva.103.023101\">10.1103/physreva.103.023101</a>","mla":"Baykusheva, Denitsa Rangelova, et al. “Strong-Field Physics in Three-Dimensional Topological Insulators.” <i>Physical Review A</i>, vol. 103, no. 2, 023101, American Physical Society, 2021, doi:<a href=\"https://doi.org/10.1103/physreva.103.023101\">10.1103/physreva.103.023101</a>.","ista":"Baykusheva DR, Chacón A, Kim D, Kim DE, Reis DA, Ghimire S. 2021. Strong-field physics in three-dimensional topological insulators. Physical Review A. 103(2), 023101."},"type":"journal_article","quality_controlled":"1","status":"public","language":[{"iso":"eng"}],"publication_status":"published","abstract":[{"text":"We investigate theoretically the strong-field regime of light-matter interactions in the topological-insulator class of quantum materials. In particular, we focus on the process of nonperturbative high-order harmonic generation from the paradigmatic three-dimensional topological insulator bismuth selenide (Bi2Se3) subjected to intense midinfrared laser fields. We analyze the contributions from the spin-orbit-coupled bulk states and the topological surface bands separately and reveal a major difference in how their harmonic yields depend on the ellipticity of the laser field. Bulk harmonics show a monotonic decrease in their yield as the ellipticity increases, in a manner reminiscent of high harmonic generation in gaseous media. However, the surface contribution exhibits a highly nontrivial dependence, culminating with a maximum for circularly polarized fields. We attribute the observed anomalous behavior to (i) the enhanced amplitude and the circular pattern of the interband dipole and the Berry connections in the vicinity of the Dirac point and (ii) the influence of the higher-order, hexagonal warping terms in the Hamiltonian, which are responsible for the hexagonal deformation of the energy surface at higher momenta. The latter are associated directly with spin-orbit-coupling parameters. Our results thus establish the sensitivity of strong-field-driven high harmonic emission to the topology of the band structure as well as to the manifestations of spin-orbit interaction.","lang":"eng"}]},{"article_number":"2111.15608","oa":1,"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","main_file_link":[{"open_access":"1","url":" https://doi.org/10.48550/arXiv.2111.15608"}],"abstract":[{"lang":"eng","text":"UVEX is a proposed medium class Explorer mission designed to provide crucial missing capabilities that will address objectives central to a broad range of modern astrophysics. The UVEX design has two co-aligned wide-field imagers operating in the FUV and NUV and a powerful broadband medium resolution spectrometer. In its two-year baseline mission, UVEX will perform a multi-cadence synoptic all-sky survey 50/100 times deeper than GALEX in the NUV/FUV, cadenced surveys of the Large and Small Magellanic Clouds, rapid target of opportunity followup, as well as spectroscopic followup of samples of stars and galaxies. The science program is built around three pillars. First, UVEX will explore the low-mass, low-metallicity galaxy frontier through imaging and spectroscopic surveys that will probe key aspects of the evolution of galaxies by understanding how star formation and stellar evolution at low metallicities affect the growth and evolution of low-metallicity, low-mass galaxies in the local universe. Such galaxies contain half the mass in the local universe, and are analogs for the first galaxies, but observed at distances that make them accessible to detailed study. Second, UVEX will explore the dynamic universe through time-domain surveys and prompt spectroscopic followup capability will probe the environments, energetics, and emission processes in the early aftermaths of gravitational wave-discovered compact object mergers, discover hot, fast UV transients, and diagnose the early stages of stellar explosions. Finally, UVEX will become a key community resource by leaving a large all-sky legacy data set, enabling a wide range of scientific studies and filling a gap in the new generation of wide-field, sensitive optical and infrared surveys provided by the Rubin, Euclid, and Roman observatories. This paper discusses the scientific potential of UVEX, and the broad scientific program."}],"publication_status":"submitted","status":"public","language":[{"iso":"eng"}],"extern":"1","type":"preprint","citation":{"chicago":"Kulkarni, S. R., Fiona A. Harrison, Brian W. Grefenstette, Hannah P. Earnshaw, Igor Andreoni, Danielle A. Berg, Joshua S. Bloom, et al. “Science with the Ultraviolet Explorer (UVEX).” <i>ArXiv</i>, n.d. <a href=\"https://doi.org/10.48550/arXiv.2111.15608\">https://doi.org/10.48550/arXiv.2111.15608</a>.","ama":"Kulkarni SR, Harrison FA, Grefenstette BW, et al. Science with the ultraviolet explorer (UVEX). <i>arXiv</i>. doi:<a href=\"https://doi.org/10.48550/arXiv.2111.15608\">10.48550/arXiv.2111.15608</a>","mla":"Kulkarni, S. R., et al. “Science with the Ultraviolet Explorer (UVEX).” <i>ArXiv</i>, 2111.15608, doi:<a href=\"https://doi.org/10.48550/arXiv.2111.15608\">10.48550/arXiv.2111.15608</a>.","ista":"Kulkarni SR, Harrison FA, Grefenstette BW, Earnshaw HP, Andreoni I, Berg DA, Bloom JS, Cenko SB, Chornock R, Christiansen JL, Coughlin MW, Criswell AW, Darvish B, Das KK, De K, Dessart L, Dixon D, Dorsman B, Kareem El-Badry KE-B, Evans C, Ford KES, Fremling C, Gansicke BT, Gezari S, Götberg YLL, Green GM, Graham MJ, Heida M, Ho AYQ, Jaodand AD, Christopher M. Johns-Krull CMJ-K, Kasliwal MM, Lazzarini M, Lu W, Margutti R, Martin DC, Masters DC, McKernan B, Naze Y, Nissanke SM, Parazin B, Perley DA, Phinney ES, Piro AL, Raaijmakers G, Rauw G, Rodriguez AC, Sana H, Senchyna P, Singer LP, Spake JJ, Stassun KG, Stern D, Teplitz HI, Weisz DR, Yao Y. Science with the ultraviolet explorer (UVEX). arXiv, 2111.15608.","short":"S.R. Kulkarni, F.A. Harrison, B.W. Grefenstette, H.P. Earnshaw, I. Andreoni, D.A. Berg, J.S. Bloom, S.B. Cenko, R. Chornock, J.L. Christiansen, M.W. Coughlin, A.W. Criswell, B. Darvish, K.K. Das, K. De, L. Dessart, D. Dixon, B. Dorsman, K.E.-B. Kareem El-Badry, C. Evans, K.E.S. Ford, C. Fremling, B.T. Gansicke, S. Gezari, Y.L.L. Götberg, G.M. Green, M.J. Graham, M. Heida, A.Y.Q. Ho, A.D. Jaodand, C.M.J.-K. Christopher M. Johns-Krull, M.M. Kasliwal, M. Lazzarini, W. Lu, R. Margutti, D.C. Martin, D.C. Masters, B. McKernan, Y. Naze, S.M. Nissanke, B. Parazin, D.A. Perley, E.S. Phinney, A.L. Piro, G. Raaijmakers, G. Rauw, A.C. Rodriguez, H. Sana, P. Senchyna, L.P. Singer, J.J. Spake, K.G. Stassun, D. Stern, H.I. Teplitz, D.R. Weisz, Y. Yao, ArXiv (n.d.).","apa":"Kulkarni, S. R., Harrison, F. A., Grefenstette, B. W., Earnshaw, H. P., Andreoni, I., Berg, D. A., … Yao, Y. (n.d.). Science with the ultraviolet explorer (UVEX). <i>arXiv</i>. <a href=\"https://doi.org/10.48550/arXiv.2111.15608\">https://doi.org/10.48550/arXiv.2111.15608</a>","ieee":"S. R. Kulkarni <i>et al.</i>, “Science with the ultraviolet explorer (UVEX),” <i>arXiv</i>. ."},"article_processing_charge":"No","year":"2021","date_published":"2021-11-30T00:00:00Z","author":[{"full_name":"Kulkarni, S. R.","last_name":"Kulkarni","first_name":"S. R."},{"first_name":"Fiona A.","full_name":"Harrison, Fiona A.","last_name":"Harrison"},{"first_name":"Brian W.","last_name":"Grefenstette","full_name":"Grefenstette, Brian W."},{"first_name":"Hannah P.","full_name":"Earnshaw, Hannah P.","last_name":"Earnshaw"},{"last_name":"Andreoni","full_name":"Andreoni, Igor","first_name":"Igor"},{"first_name":"Danielle A.","last_name":"Berg","full_name":"Berg, Danielle A."},{"last_name":"Bloom","full_name":"Bloom, Joshua S.","first_name":"Joshua S."},{"first_name":"S. Bradley","last_name":"Cenko","full_name":"Cenko, S. Bradley"},{"last_name":"Chornock","full_name":"Chornock, Ryan","first_name":"Ryan"},{"first_name":"Jessie L.","full_name":"Christiansen, Jessie L.","last_name":"Christiansen"},{"last_name":"Coughlin","full_name":"Coughlin, Michael W.","first_name":"Michael W."},{"full_name":"Criswell, Alexander Wuollet","last_name":"Criswell","first_name":"Alexander Wuollet"},{"first_name":"Behnam","full_name":"Darvish, Behnam","last_name":"Darvish"},{"first_name":"Kaustav K.","last_name":"Das","full_name":"Das, Kaustav K."},{"full_name":"De, Kishalay","last_name":"De","first_name":"Kishalay"},{"first_name":"Luc","last_name":"Dessart","full_name":"Dessart, Luc"},{"last_name":"Dixon","full_name":"Dixon, Don","first_name":"Don"},{"first_name":"Bas","last_name":"Dorsman","full_name":"Dorsman, Bas"},{"first_name":"Kareem El-Badry","last_name":"Kareem El-Badry","full_name":"Kareem El-Badry, Kareem El-Badry"},{"first_name":"Christopher","last_name":"Evans","full_name":"Evans, Christopher"},{"first_name":"K. E. Saavik","last_name":"Ford","full_name":"Ford, K. E. Saavik"},{"first_name":"Christoffer","last_name":"Fremling","full_name":"Fremling, Christoffer"},{"full_name":"Gansicke, Boris T.","last_name":"Gansicke","first_name":"Boris T."},{"full_name":"Gezari, Suvi","last_name":"Gezari","first_name":"Suvi"},{"last_name":"Götberg","full_name":"Götberg, Ylva Louise Linsdotter","orcid":"0000-0002-6960-6911","first_name":"Ylva Louise Linsdotter","id":"d0648d0c-0f64-11ee-a2e0-dd0faa2e4f7d"},{"first_name":"Gregory M.","full_name":"Green, Gregory M.","last_name":"Green"},{"last_name":"Graham","full_name":"Graham, Matthew J.","first_name":"Matthew J."},{"first_name":"Marianne","full_name":"Heida, Marianne","last_name":"Heida"},{"first_name":"Anna Y. Q.","last_name":"Ho","full_name":"Ho, Anna Y. Q."},{"first_name":"Amruta D.","full_name":"Jaodand, Amruta D.","last_name":"Jaodand"},{"first_name":"Christopher M. Johns-Krull","last_name":"Christopher M. Johns-Krull","full_name":"Christopher M. Johns-Krull, Christopher M. Johns-Krull"},{"first_name":"Mansi M.","full_name":"Kasliwal, Mansi M.","last_name":"Kasliwal"},{"last_name":"Lazzarini","full_name":"Lazzarini, Margaret","first_name":"Margaret"},{"last_name":"Lu","full_name":"Lu, Wenbin","first_name":"Wenbin"},{"first_name":"Raffaella","full_name":"Margutti, Raffaella","last_name":"Margutti"},{"last_name":"Martin","full_name":"Martin, D. Christopher","first_name":"D. Christopher"},{"first_name":"Daniel Charles","full_name":"Masters, Daniel Charles","last_name":"Masters"},{"first_name":"Barry","last_name":"McKernan","full_name":"McKernan, Barry"},{"last_name":"Naze","full_name":"Naze, Yael","first_name":"Yael"},{"first_name":"Samaya M.","last_name":"Nissanke","full_name":"Nissanke, Samaya M."},{"first_name":"B.","full_name":"Parazin, B.","last_name":"Parazin"},{"first_name":"Daniel A.","last_name":"Perley","full_name":"Perley, Daniel A."},{"first_name":"E. Sterl","full_name":"Phinney, E. Sterl","last_name":"Phinney"},{"first_name":"Anthony L.","last_name":"Piro","full_name":"Piro, Anthony L."},{"last_name":"Raaijmakers","full_name":"Raaijmakers, G.","first_name":"G."},{"first_name":"Gregor","last_name":"Rauw","full_name":"Rauw, Gregor"},{"full_name":"Rodriguez, Antonio C.","last_name":"Rodriguez","first_name":"Antonio C."},{"first_name":"Hugues","full_name":"Sana, Hugues","last_name":"Sana"},{"first_name":"Peter","last_name":"Senchyna","full_name":"Senchyna, Peter"},{"last_name":"Singer","full_name":"Singer, Leo P.","first_name":"Leo P."},{"first_name":"Jessica J.","last_name":"Spake","full_name":"Spake, Jessica J."},{"first_name":"Keivan G.","last_name":"Stassun","full_name":"Stassun, Keivan G."},{"first_name":"Daniel","full_name":"Stern, Daniel","last_name":"Stern"},{"first_name":"Harry I.","last_name":"Teplitz","full_name":"Teplitz, Harry I."},{"first_name":"Daniel R.","last_name":"Weisz","full_name":"Weisz, Daniel R."},{"first_name":"Yuhan","full_name":"Yao, Yuhan","last_name":"Yao"}],"date_updated":"2023-08-22T13:15:02Z","title":"Science with the ultraviolet explorer (UVEX)","month":"11","_id":"14097","external_id":{"arxiv":["2111.15608"]},"day":"30","date_created":"2023-08-21T10:11:00Z","publication":"arXiv","doi":"10.48550/arXiv.2111.15608","oa_version":"Preprint","arxiv":1},{"_id":"14117","date_created":"2023-08-21T12:19:30Z","external_id":{"arxiv":["2102.11107"]},"publication":"Proceedings of the IEEE","page":"612-634","date_published":"2021-05-01T00:00:00Z","article_processing_charge":"No","keyword":["Electrical and Electronic Engineering"],"title":"Toward causal representation learning","date_updated":"2023-09-11T11:43:35Z","month":"05","scopus_import":"1","extern":"1","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","issue":"5","intvolume":"       109","oa":1,"volume":109,"main_file_link":[{"open_access":"1","url":"https://doi.org/10.1109/JPROC.2021.3058954"}],"publisher":"Institute of Electrical and Electronics Engineers","day":"01","doi":"10.1109/jproc.2021.3058954","arxiv":1,"oa_version":"Published Version","author":[{"first_name":"Bernhard","full_name":"Scholkopf, Bernhard","last_name":"Scholkopf"},{"id":"26cfd52f-2483-11ee-8040-88983bcc06d4","first_name":"Francesco","last_name":"Locatello","full_name":"Locatello, Francesco","orcid":"0000-0002-4850-0683"},{"first_name":"Stefan","full_name":"Bauer, Stefan","last_name":"Bauer"},{"first_name":"Nan Rosemary","last_name":"Ke","full_name":"Ke, Nan Rosemary"},{"first_name":"Nal","last_name":"Kalchbrenner","full_name":"Kalchbrenner, Nal"},{"last_name":"Goyal","full_name":"Goyal, Anirudh","first_name":"Anirudh"},{"last_name":"Bengio","full_name":"Bengio, Yoshua","first_name":"Yoshua"}],"year":"2021","department":[{"_id":"FrLo"}],"publication_identifier":{"issn":["0018-9219"],"eissn":["1558-2256"]},"article_type":"original","citation":{"ieee":"B. Scholkopf <i>et al.</i>, “Toward causal representation learning,” <i>Proceedings of the IEEE</i>, vol. 109, no. 5. Institute of Electrical and Electronics Engineers, pp. 612–634, 2021.","apa":"Scholkopf, B., Locatello, F., Bauer, S., Ke, N. R., Kalchbrenner, N., Goyal, A., &#38; Bengio, Y. (2021). Toward causal representation learning. <i>Proceedings of the IEEE</i>. Institute of Electrical and Electronics Engineers. <a href=\"https://doi.org/10.1109/jproc.2021.3058954\">https://doi.org/10.1109/jproc.2021.3058954</a>","short":"B. Scholkopf, F. Locatello, S. Bauer, N.R. Ke, N. Kalchbrenner, A. Goyal, Y. Bengio, Proceedings of the IEEE 109 (2021) 612–634.","mla":"Scholkopf, Bernhard, et al. “Toward Causal Representation Learning.” <i>Proceedings of the IEEE</i>, vol. 109, no. 5, Institute of Electrical and Electronics Engineers, 2021, pp. 612–34, doi:<a href=\"https://doi.org/10.1109/jproc.2021.3058954\">10.1109/jproc.2021.3058954</a>.","ista":"Scholkopf B, Locatello F, Bauer S, Ke NR, Kalchbrenner N, Goyal A, Bengio Y. 2021. Toward causal representation learning. Proceedings of the IEEE. 109(5), 612–634.","chicago":"Scholkopf, Bernhard, Francesco Locatello, Stefan Bauer, Nan Rosemary Ke, Nal Kalchbrenner, Anirudh Goyal, and Yoshua Bengio. “Toward Causal Representation Learning.” <i>Proceedings of the IEEE</i>. Institute of Electrical and Electronics Engineers, 2021. <a href=\"https://doi.org/10.1109/jproc.2021.3058954\">https://doi.org/10.1109/jproc.2021.3058954</a>.","ama":"Scholkopf B, Locatello F, Bauer S, et al. Toward causal representation learning. <i>Proceedings of the IEEE</i>. 2021;109(5):612-634. doi:<a href=\"https://doi.org/10.1109/jproc.2021.3058954\">10.1109/jproc.2021.3058954</a>"},"type":"journal_article","quality_controlled":"1","publication_status":"published","abstract":[{"lang":"eng","text":"The two fields of machine learning and graphical causality arose and are developed separately. However, there is, now, cross-pollination and increasing interest in both fields to benefit from the advances of the other. In this article, we review fundamental concepts of causal inference and relate them to crucial open problems of machine learning, including transfer and generalization, thereby assaying how causality can contribute to modern machine learning research. This also applies in the opposite direction: we note that most work in causality starts from the premise that the causal variables are given. A central problem for AI and causality is, thus, causal representation learning, that is, the discovery of high-level causal variables from low-level observations. Finally, we delineate some implications of causality for machine learning and propose key research areas at the intersection of both communities."}],"language":[{"iso":"eng"}],"status":"public"},{"date_published":"2021-08-01T00:00:00Z","article_processing_charge":"No","month":"08","title":"Neighborhood contrastive learning applied to online patient monitoring","date_updated":"2023-09-11T10:16:55Z","date_created":"2023-08-22T14:03:04Z","external_id":{"arxiv":["2106.05142"]},"_id":"14176","page":"11964-11974","publication":"Proceedings of 38th International Conference on Machine Learning","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","oa":1,"intvolume":"       139","alternative_title":["PMLR"],"volume":139,"main_file_link":[{"url":"https://arxiv.org/abs/2106.05142","open_access":"1"}],"scopus_import":"1","extern":"1","author":[{"last_name":"Yèche","full_name":"Yèche, Hugo","first_name":"Hugo"},{"first_name":"Gideon","full_name":"Dresdner, Gideon","last_name":"Dresdner"},{"full_name":"Locatello, Francesco","orcid":"0000-0002-4850-0683","last_name":"Locatello","id":"26cfd52f-2483-11ee-8040-88983bcc06d4","first_name":"Francesco"},{"full_name":"Hüser, Matthias","last_name":"Hüser","first_name":"Matthias"},{"full_name":"Rätsch, Gunnar","last_name":"Rätsch","first_name":"Gunnar"}],"conference":{"start_date":"2021-07-18","location":"Virtual","end_date":"2021-07-24","name":"International Conference on Machine Learning"},"year":"2021","department":[{"_id":"FrLo"}],"day":"01","publisher":"ML Research Press","oa_version":"Preprint","arxiv":1,"quality_controlled":"1","language":[{"iso":"eng"}],"status":"public","publication_status":"published","abstract":[{"lang":"eng","text":"Intensive care units (ICU) are increasingly looking towards machine learning for methods to provide online monitoring of critically ill patients. In machine learning, online monitoring is often formulated as a supervised learning problem. Recently, contrastive learning approaches have demonstrated promising improvements over competitive supervised benchmarks. These methods rely on well-understood data augmentation techniques developed for image data which do not apply to online monitoring. In this work, we overcome this limitation by\r\nsupplementing time-series data augmentation techniques with a novel contrastive\r\nlearning objective which we call neighborhood contrastive learning (NCL). Our objective explicitly groups together contiguous time segments from each patient while maintaining state-specific information. Our experiments demonstrate a marked improvement over existing work applying contrastive methods to medical time-series."}],"citation":{"ieee":"H. Yèche, G. Dresdner, F. Locatello, M. Hüser, and G. Rätsch, “Neighborhood contrastive learning applied to online patient monitoring,” in <i>Proceedings of 38th International Conference on Machine Learning</i>, Virtual, 2021, vol. 139, pp. 11964–11974.","short":"H. Yèche, G. Dresdner, F. Locatello, M. Hüser, G. Rätsch, in:, Proceedings of 38th International Conference on Machine Learning, ML Research Press, 2021, pp. 11964–11974.","apa":"Yèche, H., Dresdner, G., Locatello, F., Hüser, M., &#38; Rätsch, G. (2021). Neighborhood contrastive learning applied to online patient monitoring. In <i>Proceedings of 38th International Conference on Machine Learning</i> (Vol. 139, pp. 11964–11974). Virtual: ML Research Press.","mla":"Yèche, Hugo, et al. “Neighborhood Contrastive Learning Applied to Online Patient Monitoring.” <i>Proceedings of 38th International Conference on Machine Learning</i>, vol. 139, ML Research Press, 2021, pp. 11964–74.","ista":"Yèche H, Dresdner G, Locatello F, Hüser M, Rätsch G. 2021. Neighborhood contrastive learning applied to online patient monitoring. Proceedings of 38th International Conference on Machine Learning. International Conference on Machine Learning, PMLR, vol. 139, 11964–11974.","chicago":"Yèche, Hugo, Gideon Dresdner, Francesco Locatello, Matthias Hüser, and Gunnar Rätsch. “Neighborhood Contrastive Learning Applied to Online Patient Monitoring.” In <i>Proceedings of 38th International Conference on Machine Learning</i>, 139:11964–74. ML Research Press, 2021.","ama":"Yèche H, Dresdner G, Locatello F, Hüser M, Rätsch G. Neighborhood contrastive learning applied to online patient monitoring. In: <i>Proceedings of 38th International Conference on Machine Learning</i>. Vol 139. ML Research Press; 2021:11964-11974."},"type":"conference"},{"status":"public","language":[{"iso":"eng"}],"publication_status":"published","abstract":[{"lang":"eng","text":"The focus of disentanglement approaches has been on identifying independent factors of variation in data. However, the causal variables underlying real-world observations are often not statistically independent. In this work, we bridge the gap to real-world scenarios by analyzing the behavior of the most prominent disentanglement approaches on correlated data in a large-scale empirical study (including 4260 models). We show and quantify that systematically induced correlations in the dataset are being learned and reflected in the latent representations, which has implications for downstream applications of disentanglement such as fairness. We also demonstrate how to resolve these latent correlations, either using weak supervision during\r\ntraining or by post-hoc correcting a pre-trained model with a small number of labels."}],"quality_controlled":"1","type":"conference","citation":{"ieee":"F. Träuble <i>et al.</i>, “On disentangled representations learned from correlated data,” in <i>Proceedings of the 38th International Conference on Machine Learning</i>, Virtual, 2021, vol. 139, pp. 10401–10412.","short":"F. Träuble, E. Creager, N. Kilbertus, F. Locatello, A. Dittadi, A. Goyal, B. Schölkopf, S. Bauer, in:, Proceedings of the 38th International Conference on Machine Learning, ML Research Press, 2021, pp. 10401–10412.","apa":"Träuble, F., Creager, E., Kilbertus, N., Locatello, F., Dittadi, A., Goyal, A., … Bauer, S. (2021). On disentangled representations learned from correlated data. In <i>Proceedings of the 38th International Conference on Machine Learning</i> (Vol. 139, pp. 10401–10412). Virtual: ML Research Press.","mla":"Träuble, Frederik, et al. “On Disentangled Representations Learned from Correlated Data.” <i>Proceedings of the 38th International Conference on Machine Learning</i>, vol. 139, ML Research Press, 2021, pp. 10401–12.","ista":"Träuble F, Creager E, Kilbertus N, Locatello F, Dittadi A, Goyal A, Schölkopf B, Bauer S. 2021. On disentangled representations learned from correlated data. Proceedings of the 38th International Conference on Machine Learning. ICML: International Conference on Machine Learning, PMLR, vol. 139, 10401–10412.","chicago":"Träuble, Frederik, Elliot Creager, Niki Kilbertus, Francesco Locatello, Andrea Dittadi, Anirudh Goyal, Bernhard Schölkopf, and Stefan Bauer. “On Disentangled Representations Learned from Correlated Data.” In <i>Proceedings of the 38th International Conference on Machine Learning</i>, 139:10401–12. ML Research Press, 2021.","ama":"Träuble F, Creager E, Kilbertus N, et al. On disentangled representations learned from correlated data. In: <i>Proceedings of the 38th International Conference on Machine Learning</i>. Vol 139. ML Research Press; 2021:10401-10412."},"department":[{"_id":"FrLo"}],"year":"2021","conference":{"name":"ICML: International Conference on Machine Learning","end_date":"2021-07-24","location":"Virtual","start_date":"2021-07-18"},"author":[{"full_name":"Träuble, Frederik","last_name":"Träuble","first_name":"Frederik"},{"first_name":"Elliot","last_name":"Creager","full_name":"Creager, Elliot"},{"first_name":"Niki","full_name":"Kilbertus, Niki","last_name":"Kilbertus"},{"last_name":"Locatello","orcid":"0000-0002-4850-0683","full_name":"Locatello, Francesco","id":"26cfd52f-2483-11ee-8040-88983bcc06d4","first_name":"Francesco"},{"full_name":"Dittadi, Andrea","last_name":"Dittadi","first_name":"Andrea"},{"first_name":"Anirudh","full_name":"Goyal, Anirudh","last_name":"Goyal"},{"first_name":"Bernhard","full_name":"Schölkopf, Bernhard","last_name":"Schölkopf"},{"first_name":"Stefan","last_name":"Bauer","full_name":"Bauer, Stefan"}],"oa_version":"Published Version","arxiv":1,"day":"01","publisher":"ML Research Press","main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/2006.07886"}],"alternative_title":["PMLR"],"volume":139,"oa":1,"intvolume":"       139","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","extern":"1","scopus_import":"1","month":"08","date_updated":"2023-09-11T10:18:48Z","title":"On disentangled representations learned from correlated data","article_processing_charge":"No","date_published":"2021-08-01T00:00:00Z","page":"10401-10412","publication":"Proceedings of the 38th International Conference on Machine Learning","external_id":{"arxiv":["2006.07886"]},"date_created":"2023-08-22T14:03:47Z","_id":"14177"},{"language":[{"iso":"eng"}],"status":"public","abstract":[{"text":"Learning meaningful representations that disentangle the underlying structure of the data generating process is considered to be of key importance in machine learning. While disentangled representations were found to be useful for diverse tasks such as abstract reasoning and fair classification, their scalability and real-world impact remain questionable. We introduce a new high-resolution dataset with 1M simulated images and over 1,800 annotated real-world images of the same setup. In contrast to previous work, this new dataset exhibits correlations, a complex underlying structure, and allows to evaluate transfer to unseen simulated and real-world settings where the encoder i) remains in distribution or ii) is out of distribution. We propose new architectures in order to scale disentangled representation learning to realistic high-resolution settings and conduct a large-scale empirical study of disentangled representations on this dataset. We observe that disentanglement is a good predictor for out-of-distribution (OOD) task performance.","lang":"eng"}],"publication_status":"published","main_file_link":[{"url":"https://arxiv.org/abs/2010.14407","open_access":"1"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","oa":1,"quality_controlled":"1","type":"conference","citation":{"ista":"Dittadi A, Träuble F, Locatello F, Wüthrich M, Agrawal V, Winther O, Bauer S, Schölkopf B. 2021. On the transfer of disentangled representations in realistic settings. The Ninth International Conference on Learning Representations. ICLR: International Conference on Learning Representations.","mla":"Dittadi, Andrea, et al. “On the Transfer of Disentangled Representations in Realistic Settings.” <i>The Ninth International Conference on Learning Representations</i>, 2021.","ama":"Dittadi A, Träuble F, Locatello F, et al. On the transfer of disentangled representations in realistic settings. In: <i>The Ninth International Conference on Learning Representations</i>. ; 2021.","chicago":"Dittadi, Andrea, Frederik Träuble, Francesco Locatello, Manuel Wüthrich, Vaibhav Agrawal, Ole Winther, Stefan Bauer, and Bernhard Schölkopf. “On the Transfer of Disentangled Representations in Realistic Settings.” In <i>The Ninth International Conference on Learning Representations</i>, 2021.","ieee":"A. Dittadi <i>et al.</i>, “On the transfer of disentangled representations in realistic settings,” in <i>The Ninth International Conference on Learning Representations</i>, Virtual, 2021.","short":"A. Dittadi, F. Träuble, F. Locatello, M. Wüthrich, V. Agrawal, O. Winther, S. Bauer, B. Schölkopf, in:, The Ninth International Conference on Learning Representations, 2021.","apa":"Dittadi, A., Träuble, F., Locatello, F., Wüthrich, M., Agrawal, V., Winther, O., … Schölkopf, B. (2021). On the transfer of disentangled representations in realistic settings. In <i>The Ninth International Conference on Learning Representations</i>. Virtual."},"extern":"1","month":"05","date_updated":"2023-09-11T10:55:30Z","title":"On the transfer of disentangled representations in realistic settings","department":[{"_id":"FrLo"}],"date_published":"2021-05-04T00:00:00Z","author":[{"first_name":"Andrea","full_name":"Dittadi, Andrea","last_name":"Dittadi"},{"first_name":"Frederik","last_name":"Träuble","full_name":"Träuble, Frederik"},{"first_name":"Francesco","id":"26cfd52f-2483-11ee-8040-88983bcc06d4","last_name":"Locatello","orcid":"0000-0002-4850-0683","full_name":"Locatello, Francesco"},{"last_name":"Wüthrich","full_name":"Wüthrich, Manuel","first_name":"Manuel"},{"first_name":"Vaibhav","last_name":"Agrawal","full_name":"Agrawal, Vaibhav"},{"first_name":"Ole","full_name":"Winther, Ole","last_name":"Winther"},{"first_name":"Stefan","full_name":"Bauer, Stefan","last_name":"Bauer"},{"full_name":"Schölkopf, Bernhard","last_name":"Schölkopf","first_name":"Bernhard"}],"article_processing_charge":"No","conference":{"location":"Virtual","start_date":"2021-05-03","end_date":"2021-05-07","name":"ICLR: International Conference on Learning Representations"},"year":"2021","arxiv":1,"oa_version":"Preprint","publication":"The Ninth International Conference on Learning Representations","date_created":"2023-08-22T14:04:16Z","external_id":{"arxiv":["2010.14407"]},"day":"04","_id":"14178"},{"article_processing_charge":"No","date_published":"2021-06-08T00:00:00Z","date_updated":"2023-09-11T10:33:19Z","title":"Self-supervised learning with data augmentations provably isolates content from style","month":"06","_id":"14179","external_id":{"arxiv":["2106.04619"]},"date_created":"2023-08-22T14:04:36Z","publication":"Advances in Neural Information Processing Systems","page":"16451-16467","intvolume":"        34","oa":1,"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","main_file_link":[{"url":"https://arxiv.org/abs/2106.04619","open_access":"1"}],"volume":34,"extern":"1","conference":{"start_date":"2021-12-07","location":"Virtual","end_date":"2021-12-10","name":"NeurIPS: Neural Information Processing Systems"},"year":"2021","author":[{"last_name":"Kügelgen","full_name":"Kügelgen, Julius von","first_name":"Julius von"},{"last_name":"Sharma","full_name":"Sharma, Yash","first_name":"Yash"},{"first_name":"Luigi","full_name":"Gresele, Luigi","last_name":"Gresele"},{"first_name":"Wieland","full_name":"Brendel, Wieland","last_name":"Brendel"},{"first_name":"Bernhard","full_name":"Schölkopf, Bernhard","last_name":"Schölkopf"},{"first_name":"Michel","full_name":"Besserve, Michel","last_name":"Besserve"},{"first_name":"Francesco","id":"26cfd52f-2483-11ee-8040-88983bcc06d4","last_name":"Locatello","orcid":"0000-0002-4850-0683","full_name":"Locatello, Francesco"}],"publication_identifier":{"isbn":["9781713845393"]},"department":[{"_id":"FrLo"}],"day":"08","oa_version":"Preprint","arxiv":1,"quality_controlled":"1","publication_status":"published","abstract":[{"text":"Self-supervised representation learning has shown remarkable success in a number of domains. A common practice is to perform data augmentation via hand-crafted transformations intended to leave the semantics of the data invariant. We seek to understand the empirical success of this approach from a theoretical perspective. We formulate the augmentation process as a latent variable model by postulating a partition of the latent representation into a content component, which is assumed invariant to augmentation, and a style component, which is allowed to change. Unlike prior work on disentanglement and independent component analysis, we allow for both nontrivial statistical and causal dependencies in the latent space. We study the identifiability of the latent representation based on pairs of views of the observations and prove sufficient conditions that allow us to identify the invariant content partition up to an invertible mapping in both generative and discriminative settings. We find numerical simulations with dependent latent variables are consistent with our theory. Lastly, we introduce Causal3DIdent, a dataset of high-dimensional, visually complex images with rich causal dependencies, which we use to study the effect of data augmentations performed in practice.","lang":"eng"}],"status":"public","language":[{"iso":"eng"}],"type":"conference","citation":{"ama":"Kügelgen J von, Sharma Y, Gresele L, et al. Self-supervised learning with data augmentations provably isolates content from style. In: <i>Advances in Neural Information Processing Systems</i>. Vol 34. ; 2021:16451-16467.","chicago":"Kügelgen, Julius von, Yash Sharma, Luigi Gresele, Wieland Brendel, Bernhard Schölkopf, Michel Besserve, and Francesco Locatello. “Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style.” In <i>Advances in Neural Information Processing Systems</i>, 34:16451–67, 2021.","mla":"Kügelgen, Julius von, et al. “Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style.” <i>Advances in Neural Information Processing Systems</i>, vol. 34, 2021, pp. 16451–67.","ista":"Kügelgen J von, Sharma Y, Gresele L, Brendel W, Schölkopf B, Besserve M, Locatello F. 2021. Self-supervised learning with data augmentations provably isolates content from style. Advances in Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems vol. 34, 16451–16467.","short":"J. von Kügelgen, Y. Sharma, L. Gresele, W. Brendel, B. Schölkopf, M. Besserve, F. Locatello, in:, Advances in Neural Information Processing Systems, 2021, pp. 16451–16467.","apa":"Kügelgen, J. von, Sharma, Y., Gresele, L., Brendel, W., Schölkopf, B., Besserve, M., &#38; Locatello, F. (2021). Self-supervised learning with data augmentations provably isolates content from style. In <i>Advances in Neural Information Processing Systems</i> (Vol. 34, pp. 16451–16467). Virtual.","ieee":"J. von Kügelgen <i>et al.</i>, “Self-supervised learning with data augmentations provably isolates content from style,” in <i>Advances in Neural Information Processing Systems</i>, Virtual, 2021, vol. 34, pp. 16451–16467."}},{"quality_controlled":"1","publication_status":"published","abstract":[{"lang":"eng","text":"Modern neural network architectures can leverage large amounts of data to generalize well within the training distribution. However, they are less capable of systematic generalization to data drawn from unseen but related distributions, a feat that is hypothesized to require compositional reasoning and reuse of knowledge. In this work, we present Neural Interpreters, an architecture that factorizes inference in a self-attention network as a system of modules, which we call \\emph{functions}. Inputs to the model are routed through a sequence of functions in a way that is end-to-end learned. The proposed architecture can flexibly compose computation along width and depth, and lends itself well to capacity extension after training. To demonstrate the versatility of Neural Interpreters, we evaluate it in two distinct settings: image classification and visual abstract reasoning on Raven Progressive Matrices. In the former, we show that Neural Interpreters perform on par with the vision transformer using fewer parameters, while being transferrable to a new task in a sample efficient manner. In the latter, we find that Neural Interpreters are competitive with respect to the state-of-the-art in terms of systematic generalization. "}],"status":"public","language":[{"iso":"eng"}],"type":"conference","citation":{"short":"N. Rahaman, M.W. Gondal, S. Joshi, P. Gehler, Y. Bengio, F. Locatello, B. Schölkopf, in:, Advances in Neural Information Processing Systems, 2021, pp. 10985–10998.","apa":"Rahaman, N., Gondal, M. W., Joshi, S., Gehler, P., Bengio, Y., Locatello, F., &#38; Schölkopf, B. (2021). Dynamic inference with neural interpreters. In <i>Advances in Neural Information Processing Systems</i> (Vol. 34, pp. 10985–10998). Virtual.","ieee":"N. Rahaman <i>et al.</i>, “Dynamic inference with neural interpreters,” in <i>Advances in Neural Information Processing Systems</i>, Virtual, 2021, vol. 34, pp. 10985–10998.","chicago":"Rahaman, Nasim, Muhammad Waleed Gondal, Shruti Joshi, Peter Gehler, Yoshua Bengio, Francesco Locatello, and Bernhard Schölkopf. “Dynamic Inference with Neural Interpreters.” In <i>Advances in Neural Information Processing Systems</i>, 34:10985–98, 2021.","ama":"Rahaman N, Gondal MW, Joshi S, et al. Dynamic inference with neural interpreters. In: <i>Advances in Neural Information Processing Systems</i>. Vol 34. ; 2021:10985-10998.","mla":"Rahaman, Nasim, et al. “Dynamic Inference with Neural Interpreters.” <i>Advances in Neural Information Processing Systems</i>, vol. 34, 2021, pp. 10985–98.","ista":"Rahaman N, Gondal MW, Joshi S, Gehler P, Bengio Y, Locatello F, Schölkopf B. 2021. Dynamic inference with neural interpreters. Advances in Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems vol. 34, 10985–10998."},"year":"2021","conference":{"name":"NeurIPS: Neural Information Processing Systems","end_date":"2021-12-10","location":"Virtual","start_date":"2021-12-07"},"author":[{"first_name":"Nasim","last_name":"Rahaman","full_name":"Rahaman, Nasim"},{"last_name":"Gondal","full_name":"Gondal, Muhammad Waleed","first_name":"Muhammad Waleed"},{"first_name":"Shruti","last_name":"Joshi","full_name":"Joshi, Shruti"},{"last_name":"Gehler","full_name":"Gehler, Peter","first_name":"Peter"},{"first_name":"Yoshua","last_name":"Bengio","full_name":"Bengio, Yoshua"},{"last_name":"Locatello","orcid":"0000-0002-4850-0683","full_name":"Locatello, Francesco","id":"26cfd52f-2483-11ee-8040-88983bcc06d4","first_name":"Francesco"},{"first_name":"Bernhard","full_name":"Schölkopf, Bernhard","last_name":"Schölkopf"}],"department":[{"_id":"FrLo"}],"publication_identifier":{"isbn":["9781713845393"]},"day":"12","oa_version":"Preprint","arxiv":1,"intvolume":"        34","oa":1,"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","main_file_link":[{"open_access":"1","url":"https://doi.org/10.48550/arXiv.2110.06399"}],"volume":34,"extern":"1","article_processing_charge":"No","date_published":"2021-10-12T00:00:00Z","title":"Dynamic inference with neural interpreters","date_updated":"2023-09-11T11:33:46Z","month":"10","_id":"14180","external_id":{"arxiv":["2110.06399"]},"date_created":"2023-08-22T14:04:55Z","publication":"Advances in Neural Information Processing Systems","page":"10985-10998"},{"date_updated":"2023-09-11T11:14:30Z","title":"Boosting variational inference with locally adaptive step-sizes","month":"05","date_published":"2021-05-19T00:00:00Z","article_processing_charge":"No","publication":"Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence","page":"2337-2343","_id":"14181","date_created":"2023-08-22T14:05:14Z","external_id":{"arxiv":["2105.09240"]},"main_file_link":[{"open_access":"1","url":"https://doi.org/10.48550/arXiv.2105.09240"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","oa":1,"extern":"1","publication_identifier":{"eisbn":["9780999241196"]},"department":[{"_id":"FrLo"}],"author":[{"full_name":"Dresdner, Gideon","last_name":"Dresdner","first_name":"Gideon"},{"full_name":"Shekhar, Saurav","last_name":"Shekhar","first_name":"Saurav"},{"first_name":"Fabian","last_name":"Pedregosa","full_name":"Pedregosa, Fabian"},{"full_name":"Locatello, Francesco","orcid":"0000-0002-4850-0683","last_name":"Locatello","id":"26cfd52f-2483-11ee-8040-88983bcc06d4","first_name":"Francesco"},{"first_name":"Gunnar","last_name":"Rätsch","full_name":"Rätsch, Gunnar"}],"year":"2021","conference":{"name":"IJCAI: International Joint Conference on Artificial Intelligence","location":"Montreal, Canada","start_date":"2021-08-19","end_date":"2021-08-27"},"doi":"10.24963/ijcai.2021/322","arxiv":1,"oa_version":"Published Version","publisher":"International Joint Conferences on Artificial Intelligence","day":"19","publication_status":"published","abstract":[{"lang":"eng","text":"Variational Inference makes a trade-off between the capacity of the variational family and the tractability of finding an approximate posterior distribution. Instead, Boosting Variational Inference allows practitioners to obtain increasingly good posterior approximations by spending more compute. The main obstacle to widespread adoption of Boosting Variational Inference is the amount of resources necessary to improve over a strong Variational Inference baseline. In our work, we trace this limitation back to the global curvature of the KL-divergence. We characterize how the global curvature impacts time and memory consumption, address the problem with the notion of local curvature, and provide a novel approximate backtracking algorithm for estimating local curvature. We give new theoretical convergence rates for our algorithms and provide experimental validation on synthetic and real-world datasets."}],"language":[{"iso":"eng"}],"status":"public","quality_controlled":"1","citation":{"apa":"Dresdner, G., Shekhar, S., Pedregosa, F., Locatello, F., &#38; Rätsch, G. (2021). Boosting variational inference with locally adaptive step-sizes. In <i>Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence</i> (pp. 2337–2343). Montreal, Canada: International Joint Conferences on Artificial Intelligence. <a href=\"https://doi.org/10.24963/ijcai.2021/322\">https://doi.org/10.24963/ijcai.2021/322</a>","short":"G. Dresdner, S. Shekhar, F. Pedregosa, F. Locatello, G. Rätsch, in:, Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, International Joint Conferences on Artificial Intelligence, 2021, pp. 2337–2343.","ieee":"G. Dresdner, S. Shekhar, F. Pedregosa, F. Locatello, and G. Rätsch, “Boosting variational inference with locally adaptive step-sizes,” in <i>Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence</i>, Montreal, Canada, 2021, pp. 2337–2343.","ama":"Dresdner G, Shekhar S, Pedregosa F, Locatello F, Rätsch G. Boosting variational inference with locally adaptive step-sizes. In: <i>Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence</i>. International Joint Conferences on Artificial Intelligence; 2021:2337-2343. doi:<a href=\"https://doi.org/10.24963/ijcai.2021/322\">10.24963/ijcai.2021/322</a>","chicago":"Dresdner, Gideon, Saurav Shekhar, Fabian Pedregosa, Francesco Locatello, and Gunnar Rätsch. “Boosting Variational Inference with Locally Adaptive Step-Sizes.” In <i>Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence</i>, 2337–43. International Joint Conferences on Artificial Intelligence, 2021. <a href=\"https://doi.org/10.24963/ijcai.2021/322\">https://doi.org/10.24963/ijcai.2021/322</a>.","ista":"Dresdner G, Shekhar S, Pedregosa F, Locatello F, Rätsch G. 2021. Boosting variational inference with locally adaptive step-sizes. Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence. IJCAI: International Joint Conference on Artificial Intelligence, 2337–2343.","mla":"Dresdner, Gideon, et al. “Boosting Variational Inference with Locally Adaptive Step-Sizes.” <i>Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence</i>, International Joint Conferences on Artificial Intelligence, 2021, pp. 2337–43, doi:<a href=\"https://doi.org/10.24963/ijcai.2021/322\">10.24963/ijcai.2021/322</a>."},"type":"conference"},{"language":[{"iso":"eng"}],"status":"public","abstract":[{"text":"When machine learning systems meet real world applications, accuracy is only\r\none of several requirements. In this paper, we assay a complementary\r\nperspective originating from the increasing availability of pre-trained and\r\nregularly improving state-of-the-art models. While new improved models develop\r\nat a fast pace, downstream tasks vary more slowly or stay constant. Assume that\r\nwe have a large unlabelled data set for which we want to maintain accurate\r\npredictions. Whenever a new and presumably better ML models becomes available,\r\nwe encounter two problems: (i) given a limited budget, which data points should\r\nbe re-evaluated using the new model?; and (ii) if the new predictions differ\r\nfrom the current ones, should we update? Problem (i) is about compute cost,\r\nwhich matters for very large data sets and models. Problem (ii) is about\r\nmaintaining consistency of the predictions, which can be highly relevant for\r\ndownstream applications; our demand is to avoid negative flips, i.e., changing\r\ncorrect to incorrect predictions. In this paper, we formalize the Prediction\r\nUpdate Problem and present an efficient probabilistic approach as answer to the\r\nabove questions. In extensive experiments on standard classification benchmark\r\ndata sets, we show that our method outperforms alternative strategies along key\r\nmetrics for backward-compatible prediction updates.","lang":"eng"}],"publication_status":"published","quality_controlled":"1","type":"conference","citation":{"ista":"Träuble F, Kügelgen J von, Kleindessner M, Locatello F, Schölkopf B, Gehler P. 2021. Backward-compatible prediction updates: A probabilistic approach. 35th Conference on Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems vol. 34, 116–128.","mla":"Träuble, Frederik, et al. “Backward-Compatible Prediction Updates: A Probabilistic Approach.” <i>35th Conference on Neural Information Processing Systems</i>, vol. 34, 2021, pp. 116–28.","chicago":"Träuble, Frederik, Julius von Kügelgen, Matthäus Kleindessner, Francesco Locatello, Bernhard Schölkopf, and Peter Gehler. “Backward-Compatible Prediction Updates: A Probabilistic Approach.” In <i>35th Conference on Neural Information Processing Systems</i>, 34:116–28, 2021.","ama":"Träuble F, Kügelgen J von, Kleindessner M, Locatello F, Schölkopf B, Gehler P. Backward-compatible prediction updates: A probabilistic approach. In: <i>35th Conference on Neural Information Processing Systems</i>. Vol 34. ; 2021:116-128.","ieee":"F. Träuble, J. von Kügelgen, M. Kleindessner, F. Locatello, B. Schölkopf, and P. Gehler, “Backward-compatible prediction updates: A probabilistic approach,” in <i>35th Conference on Neural Information Processing Systems</i>, Virtual, 2021, vol. 34, pp. 116–128.","short":"F. Träuble, J. von Kügelgen, M. Kleindessner, F. Locatello, B. Schölkopf, P. Gehler, in:, 35th Conference on Neural Information Processing Systems, 2021, pp. 116–128.","apa":"Träuble, F., Kügelgen, J. von, Kleindessner, M., Locatello, F., Schölkopf, B., &#38; Gehler, P. (2021). Backward-compatible prediction updates: A probabilistic approach. In <i>35th Conference on Neural Information Processing Systems</i> (Vol. 34, pp. 116–128). Virtual."},"publication_identifier":{"isbn":["9781713845393"]},"department":[{"_id":"FrLo"}],"author":[{"full_name":"Träuble, Frederik","last_name":"Träuble","first_name":"Frederik"},{"first_name":"Julius von","full_name":"Kügelgen, Julius von","last_name":"Kügelgen"},{"last_name":"Kleindessner","full_name":"Kleindessner, Matthäus","first_name":"Matthäus"},{"last_name":"Locatello","orcid":"0000-0002-4850-0683","full_name":"Locatello, Francesco","first_name":"Francesco","id":"26cfd52f-2483-11ee-8040-88983bcc06d4"},{"full_name":"Schölkopf, Bernhard","last_name":"Schölkopf","first_name":"Bernhard"},{"full_name":"Gehler, Peter","last_name":"Gehler","first_name":"Peter"}],"conference":{"name":"NeurIPS: Neural Information Processing Systems","start_date":"2021-12-07","location":"Virtual","end_date":"2021-12-10"},"year":"2021","oa_version":"Preprint","arxiv":1,"day":"02","volume":34,"main_file_link":[{"url":"https://arxiv.org/abs/2107.01057","open_access":"1"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","intvolume":"        34","oa":1,"extern":"1","month":"07","date_updated":"2023-09-11T11:31:59Z","title":"Backward-compatible prediction updates: A probabilistic approach","date_published":"2021-07-02T00:00:00Z","article_processing_charge":"No","page":"116-128","publication":"35th Conference on Neural Information Processing Systems","date_created":"2023-08-22T14:05:41Z","external_id":{"arxiv":["2107.01057"]},"_id":"14182"},{"type":"preprint","citation":{"mla":"Locatello, Francesco. “Enforcing and Discovering Structure in Machine Learning.” <i>ArXiv</i>, 2111.13693, doi:<a href=\"https://doi.org/10.48550/arXiv.2111.13693\">10.48550/arXiv.2111.13693</a>.","ista":"Locatello F. Enforcing and discovering structure in machine learning. arXiv, 2111.13693.","chicago":"Locatello, Francesco. “Enforcing and Discovering Structure in Machine Learning.” <i>ArXiv</i>, n.d. <a href=\"https://doi.org/10.48550/arXiv.2111.13693\">https://doi.org/10.48550/arXiv.2111.13693</a>.","ama":"Locatello F. Enforcing and discovering structure in machine learning. <i>arXiv</i>. doi:<a href=\"https://doi.org/10.48550/arXiv.2111.13693\">10.48550/arXiv.2111.13693</a>","ieee":"F. Locatello, “Enforcing and discovering structure in machine learning,” <i>arXiv</i>. .","short":"F. Locatello, ArXiv (n.d.).","apa":"Locatello, F. (n.d.). Enforcing and discovering structure in machine learning. <i>arXiv</i>. <a href=\"https://doi.org/10.48550/arXiv.2111.13693\">https://doi.org/10.48550/arXiv.2111.13693</a>"},"extern":"1","article_number":"2111.13693","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","oa":1,"publication_status":"submitted","abstract":[{"lang":"eng","text":"The world is structured in countless ways. It may be prudent to enforce corresponding structural properties to a learning algorithm's solution, such as incorporating prior beliefs, natural constraints, or causal structures. Doing so may translate to faster, more accurate, and more flexible models, which may directly relate to real-world impact. In this dissertation, we consider two different research areas that concern structuring a learning algorithm's solution: when the structure is known and when it has to be discovered."}],"main_file_link":[{"url":"https://doi.org/10.48550/arXiv.2111.13693","open_access":"1"}],"language":[{"iso":"eng"}],"status":"public","_id":"14221","date_created":"2023-08-22T14:23:35Z","external_id":{"arxiv":["2111.13693"]},"day":"26","doi":"10.48550/arXiv.2111.13693","publication":"arXiv","oa_version":"Preprint","arxiv":1,"date_published":"2021-11-26T00:00:00Z","author":[{"last_name":"Locatello","full_name":"Locatello, Francesco","orcid":"0000-0002-4850-0683","id":"26cfd52f-2483-11ee-8040-88983bcc06d4","first_name":"Francesco"}],"year":"2021","article_processing_charge":"No","title":"Enforcing and discovering structure in machine learning","date_updated":"2023-09-12T07:04:44Z","department":[{"_id":"FrLo"}],"month":"11"},{"citation":{"short":"I. Koval, ArXiv (n.d.).","apa":"Koval, I. (n.d.). Local strong Birkhoff conjecture and local spectral rigidity of almost every ellipse. <i>arXiv</i>. <a href=\"https://doi.org/10.48550/ARXIV.2111.12171\">https://doi.org/10.48550/ARXIV.2111.12171</a>","ieee":"I. Koval, “Local strong Birkhoff conjecture and local spectral rigidity of almost every ellipse,” <i>arXiv</i>. .","chicago":"Koval, Illya. “Local Strong Birkhoff Conjecture and Local Spectral Rigidity of Almost Every Ellipse.” <i>ArXiv</i>, n.d. <a href=\"https://doi.org/10.48550/ARXIV.2111.12171\">https://doi.org/10.48550/ARXIV.2111.12171</a>.","ama":"Koval I. Local strong Birkhoff conjecture and local spectral rigidity of almost every ellipse. <i>arXiv</i>. doi:<a href=\"https://doi.org/10.48550/ARXIV.2111.12171\">10.48550/ARXIV.2111.12171</a>","mla":"Koval, Illya. “Local Strong Birkhoff Conjecture and Local Spectral Rigidity of Almost Every Ellipse.” <i>ArXiv</i>, 2111.12171, doi:<a href=\"https://doi.org/10.48550/ARXIV.2111.12171\">10.48550/ARXIV.2111.12171</a>.","ista":"Koval I. Local strong Birkhoff conjecture and local spectral rigidity of almost every ellipse. arXiv, 2111.12171."},"type":"preprint","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","oa":1,"article_number":"2111.12171","language":[{"iso":"eng"}],"status":"public","abstract":[{"lang":"eng","text":"The Birkhoff conjecture says that the boundary of a strictly convex integrable billiard table is necessarily an ellipse. In this article, we consider a stronger notion of integrability, namely, integrability close to the boundary, and prove a local version of this conjecture: a small perturbation of almost every ellipse that preserves integrability near the boundary, is itself an ellipse. We apply this result to study local spectral rigidity of ellipses using the connection between the wave trace of the Laplacian and the dynamics near the boundary and establish rigidity for almost all of them."}],"publication_status":"submitted","main_file_link":[{"url":"https://doi.org/10.48550/arXiv.2111.12171","open_access":"1"}],"date_created":"2023-09-06T08:35:43Z","external_id":{"arxiv":["2111.12171"]},"day":"23","_id":"14278","oa_version":"Preprint","arxiv":1,"publication":"arXiv","doi":"10.48550/ARXIV.2111.12171","date_published":"2021-11-23T00:00:00Z","author":[{"full_name":"Koval, Illya","last_name":"Koval","id":"2eed1f3b-896a-11ed-bdf8-93c7c4bf159e","first_name":"Illya"}],"article_processing_charge":"No","year":"2021","month":"11","date_updated":"2023-09-15T06:44:00Z","title":"Local strong Birkhoff conjecture and local spectral rigidity of almost every ellipse","department":[{"_id":"GradSch"}]},{"type":"conference","citation":{"ama":"Träuble F, Dittadi A, Wuthrich M, et al. Representation learning for out-of-distribution generalization in reinforcement learning. In: <i>ICML 2021 Workshop on Unsupervised Reinforcement Learning</i>. ; 2021.","chicago":"Träuble, Frederik, Andrea Dittadi, Manuel Wuthrich, Felix Widmaier, Peter Vincent Gehler, Ole Winther, Francesco Locatello, Olivier Bachem, Bernhard Schölkopf, and Stefan Bauer. “Representation Learning for Out-of-Distribution Generalization in Reinforcement Learning.” In <i>ICML 2021 Workshop on Unsupervised Reinforcement Learning</i>, 2021.","ista":"Träuble F, Dittadi A, Wuthrich M, Widmaier F, Gehler PV, Winther O, Locatello F, Bachem O, Schölkopf B, Bauer S. 2021. Representation learning for out-of-distribution generalization in reinforcement learning. ICML 2021 Workshop on Unsupervised Reinforcement Learning. ICML: International Conference on Machine Learning.","mla":"Träuble, Frederik, et al. “Representation Learning for Out-of-Distribution Generalization in Reinforcement Learning.” <i>ICML 2021 Workshop on Unsupervised Reinforcement Learning</i>, 2021.","short":"F. Träuble, A. Dittadi, M. Wuthrich, F. Widmaier, P.V. Gehler, O. Winther, F. Locatello, O. Bachem, B. Schölkopf, S. Bauer, in:, ICML 2021 Workshop on Unsupervised Reinforcement Learning, 2021.","apa":"Träuble, F., Dittadi, A., Wuthrich, M., Widmaier, F., Gehler, P. V., Winther, O., … Bauer, S. (2021). Representation learning for out-of-distribution generalization in reinforcement learning. In <i>ICML 2021 Workshop on Unsupervised Reinforcement Learning</i>. Virtual.","ieee":"F. Träuble <i>et al.</i>, “Representation learning for out-of-distribution generalization in reinforcement learning,” in <i>ICML 2021 Workshop on Unsupervised Reinforcement Learning</i>, Virtual, 2021."},"extern":"1","language":[{"iso":"eng"}],"status":"public","abstract":[{"lang":"eng","text":"Learning data representations that are useful for various downstream tasks is a cornerstone of artificial intelligence. While existing methods are typically evaluated on downstream tasks such as classification or generative image quality, we propose to assess representations through their usefulness in downstream control tasks, such as reaching or pushing objects. By training over 10,000 reinforcement learning policies, we extensively evaluate to what extent different representation properties affect out-of-distribution (OOD) generalization. Finally, we demonstrate zero-shot transfer of these policies from simulation to the real world, without any domain randomization or fine-tuning. This paper aims to establish the first systematic characterization of the usefulness of learned representations for real-world OOD downstream tasks."}],"publication_status":"published","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","quality_controlled":"1","oa_version":"None","publication":"ICML 2021 Workshop on Unsupervised Reinforcement Learning","date_created":"2023-09-13T12:43:14Z","day":"23","_id":"14332","month":"07","date_updated":"2023-09-13T12:44:00Z","title":"Representation learning for out-of-distribution generalization in reinforcement learning","department":[{"_id":"FrLo"}],"date_published":"2021-07-23T00:00:00Z","author":[{"last_name":"Träuble","full_name":"Träuble, Frederik","first_name":"Frederik"},{"first_name":"Andrea","last_name":"Dittadi","full_name":"Dittadi, Andrea"},{"first_name":"Manuel","full_name":"Wuthrich, Manuel","last_name":"Wuthrich"},{"first_name":"Felix","last_name":"Widmaier","full_name":"Widmaier, Felix"},{"first_name":"Peter Vincent","full_name":"Gehler, Peter Vincent","last_name":"Gehler"},{"first_name":"Ole","full_name":"Winther, Ole","last_name":"Winther"},{"id":"26cfd52f-2483-11ee-8040-88983bcc06d4","first_name":"Francesco","last_name":"Locatello","full_name":"Locatello, Francesco","orcid":"0000-0002-4850-0683"},{"first_name":"Olivier","last_name":"Bachem","full_name":"Bachem, Olivier"},{"first_name":"Bernhard","full_name":"Schölkopf, Bernhard","last_name":"Schölkopf"},{"first_name":"Stefan","full_name":"Bauer, Stefan","last_name":"Bauer"}],"year":"2021","conference":{"name":"ICML: International Conference on Machine Learning","end_date":"2021-07-23","start_date":"2021-07-23","location":"Virtual"},"article_processing_charge":"No"},{"article_processing_charge":"Yes","date_published":"2021-08-16T00:00:00Z","month":"08","title":"Increased susceptibility and intrinsic apoptotic signaling in neurons by induced HDAC3 expression","date_updated":"2023-08-14T06:35:17Z","external_id":{"isi":["000695230000014"],"pmid":["34398198"]},"date_created":"2021-09-12T22:01:23Z","_id":"10000","publication":"Investigative Ophthalmology and Visual Science","file_date_updated":"2022-05-13T07:40:15Z","oa":1,"intvolume":"        62","user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","issue":"10","acknowledgement":"The authors thank Joel Dietz for maintaining the mice used in this study, Satoshi Kinoshita and the Translational Research Initiative in Pathology Laboratory at the University of Wisconsin-Madison for cutting retinal sections analyzed in this study, and Mark Banghart for statistical review of the data analysis. Supported by National Eye Institute Grants R01 EY012223 (RWN), R01 EY030123 (RWN), R01 EY029809 (LWG), R01 EY029809 (LWG) and a Vision Research CORE grant P30 EY016665, NRSA grant T32 GM081061, by an unrestricted research grant from Research to Prevent Blindness, Inc., and by a University of Wisconsin-Madison Vilas Life Cycle award and the Frederick A. Davis Research Chair (RWN). ","article_number":"14","volume":62,"scopus_import":"1","year":"2021","isi":1,"author":[{"first_name":"Heather M.","full_name":"Schmitt, Heather M.","last_name":"Schmitt"},{"last_name":"Fehrman","full_name":"Fehrman, Rachel L.","first_name":"Rachel L."},{"last_name":"Maes","full_name":"Maes, Margaret E","orcid":"0000-0001-9642-1085","first_name":"Margaret E","id":"3838F452-F248-11E8-B48F-1D18A9856A87"},{"full_name":"Yang, Huan","last_name":"Yang","first_name":"Huan"},{"last_name":"Guo","full_name":"Guo, Lian Wang","first_name":"Lian Wang"},{"full_name":"Schlamp, Cassandra L.","last_name":"Schlamp","first_name":"Cassandra L."},{"first_name":"Heather R.","last_name":"Pelzel","full_name":"Pelzel, Heather R."},{"first_name":"Robert W.","last_name":"Nickells","full_name":"Nickells, Robert W."}],"tmp":{"legal_code_url":"https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode","name":"Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)","short":"CC BY-NC-ND (4.0)","image":"/images/cc_by_nc_nd.png"},"department":[{"_id":"SaSi"}],"publication_identifier":{"eissn":["1552-5783"],"issn":["0146-0404"]},"day":"16","publisher":"Association for Research in Vision and Ophthalmology","oa_version":"Published Version","doi":"10.1167/IOVS.62.10.14","quality_controlled":"1","has_accepted_license":"1","status":"public","pmid":1,"language":[{"iso":"eng"}],"abstract":[{"lang":"eng","text":"Inhibition or targeted deletion of histone deacetylase 3 (HDAC3) is neuroprotective in a variety neurodegenerative conditions, including retinal ganglion cells (RGCs) after acute optic nerve damage. Consistent with this, induced HDAC3 expression in cultured cells shows selective toxicity to neurons. Despite an established role for HDAC3 in neuronal pathology, little is known regarding the mechanism of this pathology."}],"publication_status":"published","article_type":"original","ddc":["570"],"type":"journal_article","citation":{"mla":"Schmitt, Heather M., et al. “Increased Susceptibility and Intrinsic Apoptotic Signaling in Neurons by Induced HDAC3 Expression.” <i>Investigative Ophthalmology and Visual Science</i>, vol. 62, no. 10, 14, Association for Research in Vision and Ophthalmology, 2021, doi:<a href=\"https://doi.org/10.1167/IOVS.62.10.14\">10.1167/IOVS.62.10.14</a>.","ista":"Schmitt HM, Fehrman RL, Maes ME, Yang H, Guo LW, Schlamp CL, Pelzel HR, Nickells RW. 2021. Increased susceptibility and intrinsic apoptotic signaling in neurons by induced HDAC3 expression. Investigative Ophthalmology and Visual Science. 62(10), 14.","ama":"Schmitt HM, Fehrman RL, Maes ME, et al. Increased susceptibility and intrinsic apoptotic signaling in neurons by induced HDAC3 expression. <i>Investigative Ophthalmology and Visual Science</i>. 2021;62(10). doi:<a href=\"https://doi.org/10.1167/IOVS.62.10.14\">10.1167/IOVS.62.10.14</a>","chicago":"Schmitt, Heather M., Rachel L. Fehrman, Margaret E Maes, Huan Yang, Lian Wang Guo, Cassandra L. Schlamp, Heather R. Pelzel, and Robert W. Nickells. “Increased Susceptibility and Intrinsic Apoptotic Signaling in Neurons by Induced HDAC3 Expression.” <i>Investigative Ophthalmology and Visual Science</i>. Association for Research in Vision and Ophthalmology, 2021. <a href=\"https://doi.org/10.1167/IOVS.62.10.14\">https://doi.org/10.1167/IOVS.62.10.14</a>.","ieee":"H. M. Schmitt <i>et al.</i>, “Increased susceptibility and intrinsic apoptotic signaling in neurons by induced HDAC3 expression,” <i>Investigative Ophthalmology and Visual Science</i>, vol. 62, no. 10. Association for Research in Vision and Ophthalmology, 2021.","apa":"Schmitt, H. M., Fehrman, R. L., Maes, M. E., Yang, H., Guo, L. W., Schlamp, C. L., … Nickells, R. W. (2021). Increased susceptibility and intrinsic apoptotic signaling in neurons by induced HDAC3 expression. <i>Investigative Ophthalmology and Visual Science</i>. Association for Research in Vision and Ophthalmology. <a href=\"https://doi.org/10.1167/IOVS.62.10.14\">https://doi.org/10.1167/IOVS.62.10.14</a>","short":"H.M. Schmitt, R.L. Fehrman, M.E. Maes, H. Yang, L.W. Guo, C.L. Schlamp, H.R. Pelzel, R.W. Nickells, Investigative Ophthalmology and Visual Science 62 (2021)."},"file":[{"access_level":"open_access","success":1,"file_name":"2021_IOVS_Schmitt.pdf","file_size":19707796,"date_updated":"2022-05-13T07:40:15Z","content_type":"application/pdf","relation":"main_file","checksum":"c430967746f653aa1ae84ee617f62b73","creator":"dernst","date_created":"2022-05-13T07:40:15Z","file_id":"11369"}]},{"type":"conference","citation":{"mla":"Chatterjee, Krishnendu, et al. “Symbolic Time and Space Tradeoffs for Probabilistic Verification.” <i>Proceedings of the 36th Annual ACM/IEEE Symposium on Logic in Computer Science</i>, Institute of Electrical and Electronics Engineers, 2021, pp. 1–13, doi:<a href=\"https://doi.org/10.1109/LICS52264.2021.9470739\">10.1109/LICS52264.2021.9470739</a>.","ista":"Chatterjee K, Dvorak W, Henzinger MH, Svozil A. 2021. Symbolic time and space tradeoffs for probabilistic verification. Proceedings of the 36th Annual ACM/IEEE Symposium on Logic in Computer Science. LICS: Symposium on Logic in Computer Science, 1–13.","chicago":"Chatterjee, Krishnendu, Wolfgang Dvorak, Monika H Henzinger, and Alexander Svozil. “Symbolic Time and Space Tradeoffs for Probabilistic Verification.” In <i>Proceedings of the 36th Annual ACM/IEEE Symposium on Logic in Computer Science</i>, 1–13. Institute of Electrical and Electronics Engineers, 2021. <a href=\"https://doi.org/10.1109/LICS52264.2021.9470739\">https://doi.org/10.1109/LICS52264.2021.9470739</a>.","ama":"Chatterjee K, Dvorak W, Henzinger MH, Svozil A. Symbolic time and space tradeoffs for probabilistic verification. In: <i>Proceedings of the 36th Annual ACM/IEEE Symposium on Logic in Computer Science</i>. Institute of Electrical and Electronics Engineers; 2021:1-13. doi:<a href=\"https://doi.org/10.1109/LICS52264.2021.9470739\">10.1109/LICS52264.2021.9470739</a>","ieee":"K. Chatterjee, W. Dvorak, M. H. Henzinger, and A. Svozil, “Symbolic time and space tradeoffs for probabilistic verification,” in <i>Proceedings of the 36th Annual ACM/IEEE Symposium on Logic in Computer Science</i>, Rome, Italy, 2021, pp. 1–13.","apa":"Chatterjee, K., Dvorak, W., Henzinger, M. H., &#38; Svozil, A. (2021). Symbolic time and space tradeoffs for probabilistic verification. In <i>Proceedings of the 36th Annual ACM/IEEE Symposium on Logic in Computer Science</i> (pp. 1–13). Rome, Italy: Institute of Electrical and Electronics Engineers. <a href=\"https://doi.org/10.1109/LICS52264.2021.9470739\">https://doi.org/10.1109/LICS52264.2021.9470739</a>","short":"K. Chatterjee, W. Dvorak, M.H. Henzinger, A. Svozil, in:, Proceedings of the 36th Annual ACM/IEEE Symposium on Logic in Computer Science, Institute of Electrical and Electronics Engineers, 2021, pp. 1–13."},"quality_controlled":"1","language":[{"iso":"eng"}],"status":"public","publication_status":"published","abstract":[{"text":"We present a faster symbolic algorithm for the following central problem in probabilistic verification: Compute the maximal end-component (MEC) decomposition of Markov decision processes (MDPs). This problem generalizes the SCC decomposition problem of graphs and closed recurrent sets of Markov chains. The model of symbolic algorithms is widely used in formal verification and model-checking, where access to the input model is restricted to only symbolic operations (e.g., basic set operations and computation of one-step neighborhood). For an input MDP with  n  vertices and  m  edges, the classical symbolic algorithm from the 1990s for the MEC decomposition requires  O(n2)  symbolic operations and  O(1)  symbolic space. The only other symbolic algorithm for the MEC decomposition requires  O(nm−−√)  symbolic operations and  O(m−−√)  symbolic space. A main open question is whether the worst-case  O(n2)  bound for symbolic operations can be beaten. We present a symbolic algorithm that requires  O˜(n1.5)  symbolic operations and  O˜(n−−√)  symbolic space. Moreover, the parametrization of our algorithm provides a trade-off between symbolic operations and symbolic space: for all  0<ϵ≤1/2  the symbolic algorithm requires  O˜(n2−ϵ)  symbolic operations and  O˜(nϵ)  symbolic space ( O˜  hides poly-logarithmic factors). Using our techniques we present faster algorithms for computing the almost-sure winning regions of  ω -regular objectives for MDPs. We consider the canonical parity objectives for  ω -regular objectives, and for parity objectives with  d -priorities we present an algorithm that computes the almost-sure winning region with  O˜(n2−ϵ)  symbolic operations and  O˜(nϵ)  symbolic space, for all  0<ϵ≤1/2 .","lang":"eng"}],"day":"07","publisher":"Institute of Electrical and Electronics Engineers","arxiv":1,"oa_version":"Preprint","doi":"10.1109/LICS52264.2021.9470739","author":[{"full_name":"Chatterjee, Krishnendu","orcid":"0000-0002-4561-241X","last_name":"Chatterjee","id":"2E5DCA20-F248-11E8-B48F-1D18A9856A87","first_name":"Krishnendu"},{"full_name":"Dvorak, Wolfgang","last_name":"Dvorak","first_name":"Wolfgang"},{"first_name":"Monika H","id":"540c9bbd-f2de-11ec-812d-d04a5be85630","full_name":"Henzinger, Monika H","orcid":"0000-0002-5008-6530","last_name":"Henzinger"},{"first_name":"Alexander","last_name":"Svozil","full_name":"Svozil, Alexander"}],"isi":1,"conference":{"name":"LICS: Symposium on Logic in Computer Science","end_date":"2021-07-02","location":"Rome, Italy","start_date":"2021-06-29"},"year":"2021","department":[{"_id":"KrCh"}],"publication_identifier":{"isbn":["978-1-6654-4896-3"],"issn":["1043-6871"],"eisbn":["978-1-6654-4895-6"]},"scopus_import":"1","acknowledgement":"The authors are grateful to the anonymous referees for their valuable comments. A. S. is fully supported by the Vienna Science and Technology Fund (WWTF) through project ICT15–003. K. C. is supported by the Austrian Science Fund (FWF) NFN Grant No S11407-N23 (RiSE/SHiNE) and by the ERC CoG 863818 (ForM-SMArt). For M. H. the research leading to these results has received funding from the European Research Council under the European Unions Seventh Framework Programme (FP/2007–2013) / ERC Grant Agreement no. 340506.","user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","oa":1,"main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/2104.07466"}],"date_created":"2021-09-12T22:01:24Z","external_id":{"arxiv":["2104.07466"],"isi":["000947350400089"]},"_id":"10002","project":[{"name":"Game Theory","_id":"25863FF4-B435-11E9-9278-68D0E5697425","grant_number":"S11407","call_identifier":"FWF"},{"name":"Formal Methods for Stochastic Models: Algorithms and Applications","call_identifier":"H2020","_id":"0599E47C-7A3F-11EA-A408-12923DDC885E","grant_number":"863818"}],"page":"1-13","publication":"Proceedings of the 36th Annual ACM/IEEE Symposium on Logic in Computer Science","ec_funded":1,"date_published":"2021-07-07T00:00:00Z","keyword":["Computer science","Computational modeling","Markov processes","Probabilistic logic","Formal verification","Game Theory"],"article_processing_charge":"No","month":"07","title":"Symbolic time and space tradeoffs for probabilistic verification","date_updated":"2025-07-14T09:10:07Z"},{"project":[{"name":"Formal Methods for Stochastic Models: Algorithms and Applications","_id":"0599E47C-7A3F-11EA-A408-12923DDC885E","grant_number":"863818","call_identifier":"H2020"}],"_id":"10004","external_id":{"arxiv":["2104.07278"],"isi":["000947350400036"]},"date_created":"2021-09-12T22:01:25Z","publication":"Proceedings of the 36th Annual ACM/IEEE Symposium on Logic in Computer Science","page":"1-13","keyword":["Computer science","Heuristic algorithms","Memory management","Automata","Markov processes","Probability distribution","Complexity theory"],"article_processing_charge":"No","date_published":"2021-07-07T00:00:00Z","ec_funded":1,"date_updated":"2025-07-14T09:10:08Z","title":"Stochastic processes with expected stopping time","month":"07","scopus_import":"1","oa":1,"user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","acknowledgement":"We are grateful to the anonymous reviewers of LICS 2021 and of a previous version of this paper for insightful comments that helped improving the presentation. This research was partially supported by the grant ERC CoG 863818 (ForM-SMArt).","main_file_link":[{"url":"https://arxiv.org/abs/2104.07278","open_access":"1"}],"publisher":"Institute of Electrical and Electronics Engineers","day":"07","doi":"10.1109/LICS52264.2021.9470595","arxiv":1,"oa_version":"Preprint","conference":{"end_date":"2021-07-02","location":"Rome, Italy","start_date":"2021-06-29","name":"LICS: Symposium on Logic in Computer Science"},"year":"2021","author":[{"orcid":"0000-0002-4561-241X","full_name":"Chatterjee, Krishnendu","last_name":"Chatterjee","first_name":"Krishnendu","id":"2E5DCA20-F248-11E8-B48F-1D18A9856A87"},{"last_name":"Doyen","full_name":"Doyen, Laurent","first_name":"Laurent"}],"isi":1,"publication_identifier":{"eisbn":["978-1-6654-4895-6"],"issn":["1043-6871"],"isbn":["978-1-6654-4896-3"]},"department":[{"_id":"KrCh"}],"citation":{"ieee":"K. Chatterjee and L. Doyen, “Stochastic processes with expected stopping time,” in <i>Proceedings of the 36th Annual ACM/IEEE Symposium on Logic in Computer Science</i>, Rome, Italy, 2021, pp. 1–13.","apa":"Chatterjee, K., &#38; Doyen, L. (2021). Stochastic processes with expected stopping time. In <i>Proceedings of the 36th Annual ACM/IEEE Symposium on Logic in Computer Science</i> (pp. 1–13). Rome, Italy: Institute of Electrical and Electronics Engineers. <a href=\"https://doi.org/10.1109/LICS52264.2021.9470595\">https://doi.org/10.1109/LICS52264.2021.9470595</a>","short":"K. Chatterjee, L. Doyen, in:, Proceedings of the 36th Annual ACM/IEEE Symposium on Logic in Computer Science, Institute of Electrical and Electronics Engineers, 2021, pp. 1–13.","mla":"Chatterjee, Krishnendu, and Laurent Doyen. “Stochastic Processes with Expected Stopping Time.” <i>Proceedings of the 36th Annual ACM/IEEE Symposium on Logic in Computer Science</i>, Institute of Electrical and Electronics Engineers, 2021, pp. 1–13, doi:<a href=\"https://doi.org/10.1109/LICS52264.2021.9470595\">10.1109/LICS52264.2021.9470595</a>.","ista":"Chatterjee K, Doyen L. 2021. Stochastic processes with expected stopping time. Proceedings of the 36th Annual ACM/IEEE Symposium on Logic in Computer Science. LICS: Symposium on Logic in Computer Science, 1–13.","chicago":"Chatterjee, Krishnendu, and Laurent Doyen. “Stochastic Processes with Expected Stopping Time.” In <i>Proceedings of the 36th Annual ACM/IEEE Symposium on Logic in Computer Science</i>, 1–13. Institute of Electrical and Electronics Engineers, 2021. <a href=\"https://doi.org/10.1109/LICS52264.2021.9470595\">https://doi.org/10.1109/LICS52264.2021.9470595</a>.","ama":"Chatterjee K, Doyen L. Stochastic processes with expected stopping time. In: <i>Proceedings of the 36th Annual ACM/IEEE Symposium on Logic in Computer Science</i>. Institute of Electrical and Electronics Engineers; 2021:1-13. doi:<a href=\"https://doi.org/10.1109/LICS52264.2021.9470595\">10.1109/LICS52264.2021.9470595</a>"},"type":"conference","quality_controlled":"1","abstract":[{"lang":"eng","text":"Markov chains are the de facto finite-state model for stochastic dynamical systems, and Markov decision processes (MDPs) extend Markov chains by incorporating non-deterministic behaviors. Given an MDP and rewards on states, a classical optimization criterion is the maximal expected total reward where the MDP stops after T steps, which can be computed by a simple dynamic programming algorithm. We consider a natural generalization of the problem where the stopping times can be chosen according to a probability distribution, such that the expected stopping time is T, to optimize the expected total reward. Quite surprisingly we establish inter-reducibility of the expected stopping-time problem for Markov chains with the Positivity problem (which is related to the well-known Skolem problem), for which establishing either decidability or undecidability would be a major breakthrough. Given the hardness of the exact problem, we consider the approximate version of the problem: we show that it can be solved in exponential time for Markov chains and in exponential space for MDPs."}],"publication_status":"published","status":"public","language":[{"iso":"eng"}]},{"main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/2009.06917"}],"volume":31,"intvolume":"        31","oa":1,"issue":"09","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","acknowledgement":"M. Bulíček and J. Málek acknowledge the support of the project No. 18-12719S financed by the Czech\r\nScience foundation (GAČR). E. Maringová acknowledges support from Charles University Research program \r\nUNCE/SCI/023, the grant SVV-2020-260583 by the Ministry of Education, Youth and Sports, Czech Republic\r\nand from the Austrian Science Fund (FWF), grants P30000, W1245, and F65. M. Bulíček and J. Málek are\r\nmembers of the Nečas Center for Mathematical Modelling.\r\n","scopus_import":"1","month":"08","title":"On nonlinear problems of parabolic type with implicit constitutive equations involving flux","date_updated":"2023-09-04T11:43:45Z","article_processing_charge":"No","keyword":["Nonlinear parabolic systems","implicit constitutive theory","weak solutions","existence","uniqueness"],"date_published":"2021-08-25T00:00:00Z","publication":"Mathematical Models and Methods in Applied Sciences","external_id":{"arxiv":["2009.06917"],"isi":["000722222900004"]},"date_created":"2021-09-12T22:01:25Z","_id":"10005","project":[{"_id":"fc31cba2-9c52-11eb-aca3-ff467d239cd2","grant_number":"F6504","name":"Taming Complexity in Partial Differential Systems"}],"status":"public","language":[{"iso":"eng"}],"publication_status":"published","abstract":[{"lang":"eng","text":"We study systems of nonlinear partial differential equations of parabolic type, in which the elliptic operator is replaced by the first-order divergence operator acting on a flux function, which is related to the spatial gradient of the unknown through an additional implicit equation. This setting, broad enough in terms of applications, significantly expands the paradigm of nonlinear parabolic problems. Formulating four conditions concerning the form of the implicit equation, we first show that these conditions describe a maximal monotone p-coercive graph. We then establish the global-in-time and large-data existence of a (weak) solution and its uniqueness. To this end, we adopt and significantly generalize Minty’s method of monotone mappings. A unified theory, containing several novel tools, is developed in a way to be tractable from the point of view of numerical approximations."}],"quality_controlled":"1","citation":{"mla":"Bulíček, Miroslav, et al. “On Nonlinear Problems of Parabolic Type with Implicit Constitutive Equations Involving Flux.” <i>Mathematical Models and Methods in Applied Sciences</i>, vol. 31, no. 09, World Scientific, 2021, doi:<a href=\"https://doi.org/10.1142/S0218202521500457\">10.1142/S0218202521500457</a>.","ista":"Bulíček M, Maringová E, Málek J. 2021. On nonlinear problems of parabolic type with implicit constitutive equations involving flux. Mathematical Models and Methods in Applied Sciences. 31(09).","chicago":"Bulíček, Miroslav, Erika Maringová, and Josef Málek. “On Nonlinear Problems of Parabolic Type with Implicit Constitutive Equations Involving Flux.” <i>Mathematical Models and Methods in Applied Sciences</i>. World Scientific, 2021. <a href=\"https://doi.org/10.1142/S0218202521500457\">https://doi.org/10.1142/S0218202521500457</a>.","ama":"Bulíček M, Maringová E, Málek J. On nonlinear problems of parabolic type with implicit constitutive equations involving flux. <i>Mathematical Models and Methods in Applied Sciences</i>. 2021;31(09). doi:<a href=\"https://doi.org/10.1142/S0218202521500457\">10.1142/S0218202521500457</a>","ieee":"M. Bulíček, E. Maringová, and J. Málek, “On nonlinear problems of parabolic type with implicit constitutive equations involving flux,” <i>Mathematical Models and Methods in Applied Sciences</i>, vol. 31, no. 09. World Scientific, 2021.","short":"M. Bulíček, E. Maringová, J. Málek, Mathematical Models and Methods in Applied Sciences 31 (2021).","apa":"Bulíček, M., Maringová, E., &#38; Málek, J. (2021). On nonlinear problems of parabolic type with implicit constitutive equations involving flux. <i>Mathematical Models and Methods in Applied Sciences</i>. World Scientific. <a href=\"https://doi.org/10.1142/S0218202521500457\">https://doi.org/10.1142/S0218202521500457</a>"},"type":"journal_article","article_type":"original","publication_identifier":{"issn":["0218-2025"],"eissn":["1793-6314"]},"department":[{"_id":"JuFi"}],"year":"2021","isi":1,"author":[{"full_name":"Bulíček, Miroslav","last_name":"Bulíček","first_name":"Miroslav"},{"last_name":"Maringová","full_name":"Maringová, Erika","id":"dbabca31-66eb-11eb-963a-fb9c22c880b4","first_name":"Erika"},{"full_name":"Málek, Josef","last_name":"Málek","first_name":"Josef"}],"oa_version":"Preprint","arxiv":1,"doi":"10.1142/S0218202521500457","day":"25","publisher":"World Scientific"},{"publisher":"Institute of Science and Technology Austria","day":"14","doi":"10.15479/at:ista:10007","oa_version":"Published Version","author":[{"last_name":"Hensel","full_name":"Hensel, Sebastian","orcid":"0000-0001-7252-8072","id":"4D23B7DA-F248-11E8-B48F-1D18A9856A87","first_name":"Sebastian"}],"year":"2021","degree_awarded":"PhD","publication_identifier":{"issn":["2663-337X"]},"department":[{"_id":"GradSch"},{"_id":"JuFi"}],"ddc":["515"],"file":[{"date_updated":"2021-09-15T14:37:30Z","content_type":"application/x-zip-compressed","file_size":15022154,"relation":"source_file","checksum":"c8475faaf0b680b4971f638f1db16347","access_level":"closed","file_name":"thesis_final_Hensel.zip","file_id":"10008","creator":"shensel","date_created":"2021-09-13T11:03:24Z"},{"content_type":"application/pdf","date_updated":"2021-09-14T09:52:47Z","file_size":6583638,"relation":"main_file","checksum":"1a609937aa5275452822f45f2da17f07","access_level":"open_access","file_name":"thesis_final_Hensel.pdf","file_id":"10014","date_created":"2021-09-13T14:18:56Z","creator":"shensel"}],"type":"dissertation","citation":{"apa":"Hensel, S. (2021). <i>Curvature driven interface evolution: Uniqueness properties of weak solution concepts</i>. Institute of Science and Technology Austria. <a href=\"https://doi.org/10.15479/at:ista:10007\">https://doi.org/10.15479/at:ista:10007</a>","short":"S. Hensel, Curvature Driven Interface Evolution: Uniqueness Properties of Weak Solution Concepts, Institute of Science and Technology Austria, 2021.","ieee":"S. Hensel, “Curvature driven interface evolution: Uniqueness properties of weak solution concepts,” Institute of Science and Technology Austria, 2021.","chicago":"Hensel, Sebastian. “Curvature Driven Interface Evolution: Uniqueness Properties of Weak Solution Concepts.” Institute of Science and Technology Austria, 2021. <a href=\"https://doi.org/10.15479/at:ista:10007\">https://doi.org/10.15479/at:ista:10007</a>.","ama":"Hensel S. Curvature driven interface evolution: Uniqueness properties of weak solution concepts. 2021. doi:<a href=\"https://doi.org/10.15479/at:ista:10007\">10.15479/at:ista:10007</a>","ista":"Hensel S. 2021. Curvature driven interface evolution: Uniqueness properties of weak solution concepts. Institute of Science and Technology Austria.","mla":"Hensel, Sebastian. <i>Curvature Driven Interface Evolution: Uniqueness Properties of Weak Solution Concepts</i>. Institute of Science and Technology Austria, 2021, doi:<a href=\"https://doi.org/10.15479/at:ista:10007\">10.15479/at:ista:10007</a>."},"publication_status":"published","abstract":[{"text":"The present thesis is concerned with the derivation of weak-strong uniqueness principles for curvature driven interface evolution problems not satisfying a comparison principle. The specific examples being treated are two-phase Navier-Stokes flow with surface tension, modeling the evolution of two incompressible, viscous and immiscible fluids separated by a sharp interface, and multiphase mean curvature flow, which serves as an idealized model for the motion of grain boundaries in an annealing polycrystalline material. Our main results - obtained in joint works with Julian Fischer, Tim Laux and Theresa M. Simon - state that prior to the formation of geometric singularities due to topology changes, the weak solution concept of Abels (Interfaces Free Bound. 9, 2007) to two-phase Navier-Stokes flow with surface tension and the weak solution concept of Laux and Otto (Calc. Var. Partial Differential Equations 55, 2016) to multiphase mean curvature flow (for networks in R^2 or double bubbles in R^3) represents the unique solution to these interface evolution problems within the class of classical solutions, respectively. To the best of the author's knowledge, for interface evolution problems not admitting a geometric comparison principle the derivation of a weak-strong uniqueness principle represented an open problem, so that the works contained in the present thesis constitute the first positive results in this direction. The key ingredient of our approach consists of the introduction of a novel concept of relative entropies for a class of curvature driven interface evolution problems, for which the associated energy contains an interfacial contribution being proportional to the surface area of the evolving (network of) interface(s). The interfacial part of the relative entropy gives sufficient control on the interface error between a weak and a classical solution, and its time evolution can be computed, at least in principle, for any energy dissipating weak solution concept. A resulting stability estimate for the relative entropy essentially entails the above mentioned weak-strong uniqueness principles. The present thesis contains a detailed introduction to our relative entropy approach, which in particular highlights potential applications to other problems in curvature driven interface evolution not treated in this thesis.","lang":"eng"}],"language":[{"iso":"eng"}],"status":"public","has_accepted_license":"1","_id":"10007","project":[{"grant_number":"665385","_id":"2564DBCA-B435-11E9-9278-68D0E5697425","call_identifier":"H2020","name":"International IST Doctoral Program"},{"call_identifier":"H2020","_id":"0aa76401-070f-11eb-9043-b5bb049fa26d","grant_number":"948819","name":"Bridging Scales in Random Materials"}],"date_created":"2021-09-13T11:12:34Z","file_date_updated":"2021-09-15T14:37:30Z","supervisor":[{"last_name":"Fischer","orcid":"0000-0002-0479-558X","full_name":"Fischer, Julian L","first_name":"Julian L","id":"2C12A0B0-F248-11E8-B48F-1D18A9856A87"}],"page":"300","date_published":"2021-09-14T00:00:00Z","article_processing_charge":"No","ec_funded":1,"title":"Curvature driven interface evolution: Uniqueness properties of weak solution concepts","date_updated":"2023-09-07T13:30:45Z","month":"09","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","oa":1,"alternative_title":["ISTA Thesis"],"related_material":{"record":[{"status":"public","relation":"part_of_dissertation","id":"10012"},{"relation":"part_of_dissertation","status":"public","id":"10013"},{"id":"7489","status":"public","relation":"part_of_dissertation"}]}},{"citation":{"ieee":"S. Hensel and T. Laux, “A new varifold solution concept for mean curvature flow: Convergence of  the Allen-Cahn equation and weak-strong uniqueness,” <i>arXiv</i>. .","apa":"Hensel, S., &#38; Laux, T. (n.d.). A new varifold solution concept for mean curvature flow: Convergence of  the Allen-Cahn equation and weak-strong uniqueness. <i>arXiv</i>. <a href=\"https://doi.org/10.48550/arXiv.2109.04233\">https://doi.org/10.48550/arXiv.2109.04233</a>","short":"S. Hensel, T. Laux, ArXiv (n.d.).","ista":"Hensel S, Laux T. A new varifold solution concept for mean curvature flow: Convergence of  the Allen-Cahn equation and weak-strong uniqueness. arXiv, 2109.04233.","mla":"Hensel, Sebastian, and Tim Laux. “A New Varifold Solution Concept for Mean Curvature Flow: Convergence of  the Allen-Cahn Equation and Weak-Strong Uniqueness.” <i>ArXiv</i>, 2109.04233, doi:<a href=\"https://doi.org/10.48550/arXiv.2109.04233\">10.48550/arXiv.2109.04233</a>.","chicago":"Hensel, Sebastian, and Tim Laux. “A New Varifold Solution Concept for Mean Curvature Flow: Convergence of  the Allen-Cahn Equation and Weak-Strong Uniqueness.” <i>ArXiv</i>, n.d. <a href=\"https://doi.org/10.48550/arXiv.2109.04233\">https://doi.org/10.48550/arXiv.2109.04233</a>.","ama":"Hensel S, Laux T. A new varifold solution concept for mean curvature flow: Convergence of  the Allen-Cahn equation and weak-strong uniqueness. <i>arXiv</i>. doi:<a href=\"https://doi.org/10.48550/arXiv.2109.04233\">10.48550/arXiv.2109.04233</a>"},"type":"preprint","main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/2109.04233"}],"abstract":[{"text":"We propose a new weak solution concept for (two-phase) mean curvature flow which enjoys both (unconditional) existence and (weak-strong) uniqueness properties. These solutions are evolving varifolds, just as in Brakke's formulation, but are coupled to the phase volumes by a simple transport equation. First, we show that, in the exact same setup as in Ilmanen's proof [J. Differential Geom. 38, 417-461, (1993)], any limit point of solutions to the Allen-Cahn equation is a varifold solution in our sense. Second, we prove that any calibrated flow in the sense of Fischer et al. [arXiv:2003.05478] - and hence any classical solution to mean curvature flow - is unique in the class of our new varifold solutions. This is in sharp contrast to the case of Brakke flows, which a priori may disappear at any given time and are therefore fatally non-unique. Finally, we propose an extension of the solution concept to the multi-phase case which is at least guaranteed to satisfy a weak-strong uniqueness principle.","lang":"eng"}],"publication_status":"submitted","status":"public","language":[{"iso":"eng"}],"article_number":"2109.04233","oa":1,"acknowledgement":"This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 948819), and from the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy – EXC-2047/1 – 390685813. The content of this paper was developed and parts of it were written during a visit of the first author to the Hausdorff Center of Mathematics (HCM), University of Bonn. The hospitality and the support of HCM are gratefully acknowledged.","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","doi":"10.48550/arXiv.2109.04233","publication":"arXiv","arxiv":1,"oa_version":"Preprint","project":[{"call_identifier":"H2020","_id":"0aa76401-070f-11eb-9043-b5bb049fa26d","grant_number":"948819","name":"Bridging Scales in Random Materials"}],"_id":"10011","day":"09","external_id":{"arxiv":["2109.04233"]},"date_created":"2021-09-13T12:17:10Z","department":[{"_id":"JuFi"}],"title":"A new varifold solution concept for mean curvature flow: Convergence of  the Allen-Cahn equation and weak-strong uniqueness","date_updated":"2023-05-03T10:34:38Z","month":"09","keyword":["Mean curvature flow","gradient flows","varifolds","weak solutions","weak-strong uniqueness","calibrated geometry","gradient-flow calibrations"],"year":"2021","article_processing_charge":"No","date_published":"2021-09-09T00:00:00Z","author":[{"last_name":"Hensel","orcid":"0000-0001-7252-8072","full_name":"Hensel, Sebastian","id":"4D23B7DA-F248-11E8-B48F-1D18A9856A87","first_name":"Sebastian"},{"first_name":"Tim","full_name":"Laux, Tim","last_name":"Laux"}],"ec_funded":1}]