[{"_id":"13459","oa_version":"Preprint","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","article_number":"248","quality_controlled":"1","date_updated":"2023-08-21T11:35:50Z","status":"public","main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/2103.13642"}],"month":"05","publication_status":"published","volume":161,"type":"journal_article","scopus_import":"1","keyword":["Space and Planetary Science","Astronomy and Astrophysics"],"publication":"The Astronomical Journal","language":[{"iso":"eng"}],"extern":"1","citation":{"ieee":"L. Wang <i>et al.</i>, “The detection and characterization of Be+sdO binaries from HST/STIS FUV spectroscopy,” <i>The Astronomical Journal</i>, vol. 161, no. 5. American Astronomical Society, 2021.","ista":"Wang L, Gies DR, Peters GJ, Götberg YLL, Chojnowski SD, Lester KV, Howell SB. 2021. The detection and characterization of Be+sdO binaries from HST/STIS FUV spectroscopy. The Astronomical Journal. 161(5), 248.","chicago":"Wang, Luqian, Douglas R. Gies, Geraldine J. Peters, Ylva Louise Linsdotter Götberg, S. Drew Chojnowski, Kathryn V. Lester, and Steve B. Howell. “The Detection and Characterization of Be+sdO Binaries from HST/STIS FUV Spectroscopy.” <i>The Astronomical Journal</i>. American Astronomical Society, 2021. <a href=\"https://doi.org/10.3847/1538-3881/abf144\">https://doi.org/10.3847/1538-3881/abf144</a>.","apa":"Wang, L., Gies, D. R., Peters, G. J., Götberg, Y. L. L., Chojnowski, S. D., Lester, K. V., &#38; Howell, S. B. (2021). The detection and characterization of Be+sdO binaries from HST/STIS FUV spectroscopy. <i>The Astronomical Journal</i>. American Astronomical Society. <a href=\"https://doi.org/10.3847/1538-3881/abf144\">https://doi.org/10.3847/1538-3881/abf144</a>","short":"L. Wang, D.R. Gies, G.J. Peters, Y.L.L. Götberg, S.D. Chojnowski, K.V. Lester, S.B. Howell, The Astronomical Journal 161 (2021).","ama":"Wang L, Gies DR, Peters GJ, et al. The detection and characterization of Be+sdO binaries from HST/STIS FUV spectroscopy. <i>The Astronomical Journal</i>. 2021;161(5). doi:<a href=\"https://doi.org/10.3847/1538-3881/abf144\">10.3847/1538-3881/abf144</a>","mla":"Wang, Luqian, et al. “The Detection and Characterization of Be+sdO Binaries from HST/STIS FUV Spectroscopy.” <i>The Astronomical Journal</i>, vol. 161, no. 5, 248, American Astronomical Society, 2021, doi:<a href=\"https://doi.org/10.3847/1538-3881/abf144\">10.3847/1538-3881/abf144</a>."},"article_processing_charge":"No","publisher":"American Astronomical Society","title":"The detection and characterization of Be+sdO binaries from HST/STIS FUV spectroscopy","date_created":"2023-08-03T10:11:57Z","year":"2021","intvolume":"       161","external_id":{"arxiv":["2103.13642"]},"publication_identifier":{"eissn":["1538-3881"],"issn":["0004-6256"]},"article_type":"original","issue":"5","doi":"10.3847/1538-3881/abf144","abstract":[{"text":"The B emission-line stars are rapid rotators that were probably spun up by mass and angular momentum accretion through mass transfer in an interacting binary. Mass transfer will strip the donor star of its envelope to create a small and hot subdwarf remnant. Here we report on Hubble Space Telescope/STIS far-ultraviolet spectroscopy of a sample of Be stars that reveals the presence of the hot sdO companion through the calculation of cross-correlation functions of the observed and model spectra. We clearly detect the spectral signature of the sdO star in 10 of the 13 stars in the sample, and the spectral signals indicate that the sdO stars are hot, relatively faint, and slowly rotating as predicted by models. A comparison of their temperatures and radii with evolutionary tracks indicates that the sdO stars occupy the relatively long-lived, He-core burning stage. Only 1 of the 10 detections was a known binary prior to this investigation, which emphasizes the difficulty of finding such Be+sdO binaries through optical spectroscopy. However, these results and others indicate that many Be stars probably host hot subdwarf companions.","lang":"eng"}],"day":"04","date_published":"2021-05-04T00:00:00Z","author":[{"first_name":"Luqian","full_name":"Wang, Luqian","last_name":"Wang"},{"first_name":"Douglas R.","full_name":"Gies, Douglas R.","last_name":"Gies"},{"last_name":"Peters","first_name":"Geraldine J.","full_name":"Peters, Geraldine J."},{"orcid":"0000-0002-6960-6911","first_name":"Ylva Louise Linsdotter","full_name":"Götberg, Ylva Louise Linsdotter","last_name":"Götberg","id":"d0648d0c-0f64-11ee-a2e0-dd0faa2e4f7d"},{"full_name":"Chojnowski, S. Drew","first_name":"S. Drew","last_name":"Chojnowski"},{"first_name":"Kathryn V.","full_name":"Lester, Kathryn V.","last_name":"Lester"},{"last_name":"Howell","full_name":"Howell, Steve B.","first_name":"Steve B."}],"arxiv":1,"oa":1},{"abstract":[{"lang":"eng","text":"Shape resonances play a central role in many areas of science, but the real-time measurement of the associated many-body dynamics remains challenging. Here, we present measurements of recoil frame angle-resolved photoionization delays in the vicinity of shape resonances of CF4. This technique provides insights into the spatiotemporal photoionization dynamics of molecular shape resonances. We find delays of up to ∼600 as in the ionization out of the highest occupied molecular orbital (HOMO) with a strong dependence on the emission direction and a pronounced asymmetry along the dissociation axis. Comparison with quantum-scattering calculations traces the asymmetries to the interference of a small subset of partial waves at low kinetic energies and, additionally, to the interference of two overlapping shape resonances in the HOMO-1 channel. Our experimental and theoretical results establish a broadly applicable approach to space- and time-resolved photoionization dynamics in the molecular frame."}],"day":"03","date_published":"2021-12-03T00:00:00Z","author":[{"first_name":"Saijoscha","full_name":"Heck, Saijoscha","last_name":"Heck"},{"last_name":"Baykusheva","id":"71b4d059-2a03-11ee-914d-dfa3beed6530","first_name":"Denitsa Rangelova","full_name":"Baykusheva, Denitsa Rangelova"},{"full_name":"Han, Meng","first_name":"Meng","last_name":"Han"},{"last_name":"Ji","first_name":"Jia-Bao","full_name":"Ji, Jia-Bao"},{"full_name":"Perry, Conaill","first_name":"Conaill","last_name":"Perry"},{"last_name":"Gong","first_name":"Xiaochun","full_name":"Gong, Xiaochun"},{"last_name":"Wörner","first_name":"Hans Jakob","full_name":"Wörner, Hans Jakob"}],"oa":1,"article_type":"original","issue":"49","doi":"10.1126/sciadv.abj8121","title":"Attosecond interferometry of shape resonances in the recoil frame of CF4","pmid":1,"year":"2021","date_created":"2023-08-09T13:09:02Z","intvolume":"         7","external_id":{"pmid":["34860540"]},"publication_identifier":{"eissn":["2375-2548"]},"citation":{"mla":"Heck, Saijoscha, et al. “Attosecond Interferometry of Shape Resonances in the Recoil Frame of CF4.” <i>Science Advances</i>, vol. 7, no. 49, abj8121, American Association for the Advancement of Science, 2021, doi:<a href=\"https://doi.org/10.1126/sciadv.abj8121\">10.1126/sciadv.abj8121</a>.","ama":"Heck S, Baykusheva DR, Han M, et al. Attosecond interferometry of shape resonances in the recoil frame of CF4. <i>Science Advances</i>. 2021;7(49). doi:<a href=\"https://doi.org/10.1126/sciadv.abj8121\">10.1126/sciadv.abj8121</a>","short":"S. Heck, D.R. Baykusheva, M. Han, J.-B. Ji, C. Perry, X. Gong, H.J. Wörner, Science Advances 7 (2021).","apa":"Heck, S., Baykusheva, D. R., Han, M., Ji, J.-B., Perry, C., Gong, X., &#38; Wörner, H. J. (2021). Attosecond interferometry of shape resonances in the recoil frame of CF4. <i>Science Advances</i>. American Association for the Advancement of Science. <a href=\"https://doi.org/10.1126/sciadv.abj8121\">https://doi.org/10.1126/sciadv.abj8121</a>","chicago":"Heck, Saijoscha, Denitsa Rangelova Baykusheva, Meng Han, Jia-Bao Ji, Conaill Perry, Xiaochun Gong, and Hans Jakob Wörner. “Attosecond Interferometry of Shape Resonances in the Recoil Frame of CF4.” <i>Science Advances</i>. American Association for the Advancement of Science, 2021. <a href=\"https://doi.org/10.1126/sciadv.abj8121\">https://doi.org/10.1126/sciadv.abj8121</a>.","ista":"Heck S, Baykusheva DR, Han M, Ji J-B, Perry C, Gong X, Wörner HJ. 2021. Attosecond interferometry of shape resonances in the recoil frame of CF4. Science Advances. 7(49), abj8121.","ieee":"S. Heck <i>et al.</i>, “Attosecond interferometry of shape resonances in the recoil frame of CF4,” <i>Science Advances</i>, vol. 7, no. 49. American Association for the Advancement of Science, 2021."},"extern":"1","publisher":"American Association for the Advancement of Science","article_processing_charge":"No","keyword":["Multidisciplinary"],"publication":"Science Advances","language":[{"iso":"eng"}],"type":"journal_article","scopus_import":"1","status":"public","date_updated":"2024-10-14T12:23:37Z","main_file_link":[{"open_access":"1","url":"https://doi.org/10.1126/sciadv.abj8121"}],"volume":7,"publication_status":"published","month":"12","_id":"13995","oa_version":"Published Version","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","article_number":"abj8121","quality_controlled":"1"},{"day":"22","abstract":[{"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.","lang":"eng"}],"author":[{"first_name":"Denitsa Rangelova","full_name":"Baykusheva, Denitsa Rangelova","last_name":"Baykusheva","id":"71b4d059-2a03-11ee-914d-dfa3beed6530"},{"last_name":"Chacón","full_name":"Chacón, Alexis","first_name":"Alexis"},{"full_name":"Lu, Jian","first_name":"Jian","last_name":"Lu"},{"last_name":"Bailey","full_name":"Bailey, Trevor P.","first_name":"Trevor P."},{"first_name":"Jonathan A.","full_name":"Sobota, Jonathan A.","last_name":"Sobota"},{"last_name":"Soifer","first_name":"Hadas","full_name":"Soifer, Hadas"},{"last_name":"Kirchmann","first_name":"Patrick S.","full_name":"Kirchmann, Patrick S."},{"first_name":"Costel","full_name":"Rotundu, Costel","last_name":"Rotundu"},{"last_name":"Uher","full_name":"Uher, Ctirad","first_name":"Ctirad"},{"last_name":"Heinz","first_name":"Tony F.","full_name":"Heinz, Tony F."},{"last_name":"Reis","first_name":"David A.","full_name":"Reis, David A."},{"last_name":"Ghimire","first_name":"Shambhu","full_name":"Ghimire, Shambhu"}],"arxiv":1,"oa":1,"date_published":"2021-10-22T00:00:00Z","issue":"21","article_type":"original","doi":"10.1021/acs.nanolett.1c02145","title":"All-optical probe of three-dimensional topological insulators based on high-harmonic generation by circularly polarized laser fields","pmid":1,"external_id":{"pmid":["34676752"],"arxiv":["2109.15291"]},"publication_identifier":{"issn":["1530-6984"],"eissn":["1530-6992"]},"year":"2021","date_created":"2023-08-09T13:09:15Z","intvolume":"        21","article_processing_charge":"No","publisher":"American Chemical Society","citation":{"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>.","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>","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.","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>","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>.","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.","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."},"extern":"1","publication":"Nano Letters","keyword":["Mechanical Engineering","Condensed Matter Physics","General Materials Science","General Chemistry","Bioengineering"],"language":[{"iso":"eng"}],"type":"journal_article","scopus_import":"1","main_file_link":[{"open_access":"1","url":"https://doi.org/10.1021/acs.nanolett.1c02145"}],"date_updated":"2024-10-14T12:26:13Z","status":"public","publication_status":"published","month":"10","volume":21,"page":"8970-8978","_id":"13996","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","oa_version":"Published Version","quality_controlled":"1"},{"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"}],"day":"01","date_published":"2021-02-01T00:00:00Z","arxiv":1,"author":[{"first_name":"Denitsa Rangelova","full_name":"Baykusheva, Denitsa Rangelova","id":"71b4d059-2a03-11ee-914d-dfa3beed6530","last_name":"Baykusheva"},{"last_name":"Chacón","full_name":"Chacón, Alexis","first_name":"Alexis"},{"full_name":"Kim, Dasol","first_name":"Dasol","last_name":"Kim"},{"last_name":"Kim","first_name":"Dong Eon","full_name":"Kim, Dong Eon"},{"first_name":"David A.","full_name":"Reis, David A.","last_name":"Reis"},{"last_name":"Ghimire","first_name":"Shambhu","full_name":"Ghimire, Shambhu"}],"oa":1,"article_type":"original","issue":"2","doi":"10.1103/physreva.103.023101","title":"Strong-field physics in three-dimensional topological insulators","date_created":"2023-08-09T13:09:26Z","year":"2021","intvolume":"       103","external_id":{"arxiv":["2008.01265"]},"publication_identifier":{"eissn":["2469-9934"],"issn":["2469-9926"]},"extern":"1","citation":{"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.","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.","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>.","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>","short":"D.R. Baykusheva, A. Chacón, D. Kim, D.E. Kim, D.A. Reis, S. Ghimire, Physical Review A 103 (2021).","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>.","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>"},"publisher":"American Physical Society","article_processing_charge":"No","publication":"Physical Review A","language":[{"iso":"eng"}],"type":"journal_article","scopus_import":"1","status":"public","date_updated":"2024-10-14T12:26:26Z","main_file_link":[{"url":"https://arxiv.org/abs/2008.01265","open_access":"1"}],"publication_status":"published","volume":103,"month":"02","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","_id":"13997","oa_version":"Preprint","article_number":"023101","quality_controlled":"1"},{"article_processing_charge":"No","related_material":{"link":[{"description":"News on ISTA website","relation":"press_release","url":"https://ista.ac.at/en/news/deep-mapping-the-night-sky-for-hot-stars/"}]},"citation":{"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.","ieee":"S. R. Kulkarni <i>et al.</i>, “Science with the ultraviolet explorer (UVEX),” <i>arXiv</i>. .","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>.","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>","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.).","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>.","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>"},"extern":"1","article_number":"2111.15608","oa_version":"Preprint","_id":"14097","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","month":"11","publication_status":"submitted","external_id":{"arxiv":["2111.15608"]},"date_created":"2023-08-21T10:11:00Z","year":"2021","main_file_link":[{"open_access":"1","url":" https://doi.org/10.48550/arXiv.2111.15608"}],"title":"Science with the ultraviolet explorer (UVEX)","date_updated":"2024-07-16T12:30:12Z","status":"public","doi":"10.48550/arXiv.2111.15608","type":"preprint","oa":1,"arxiv":1,"language":[{"iso":"eng"}],"author":[{"last_name":"Kulkarni","first_name":"S. R.","full_name":"Kulkarni, S. R."},{"first_name":"Fiona A.","full_name":"Harrison, Fiona A.","last_name":"Harrison"},{"last_name":"Grefenstette","first_name":"Brian W.","full_name":"Grefenstette, Brian W."},{"last_name":"Earnshaw","full_name":"Earnshaw, Hannah P.","first_name":"Hannah P."},{"last_name":"Andreoni","first_name":"Igor","full_name":"Andreoni, Igor"},{"last_name":"Berg","full_name":"Berg, Danielle A.","first_name":"Danielle A."},{"first_name":"Joshua S.","full_name":"Bloom, Joshua S.","last_name":"Bloom"},{"last_name":"Cenko","first_name":"S. Bradley","full_name":"Cenko, S. Bradley"},{"last_name":"Chornock","first_name":"Ryan","full_name":"Chornock, Ryan"},{"full_name":"Christiansen, Jessie L.","first_name":"Jessie L.","last_name":"Christiansen"},{"last_name":"Coughlin","full_name":"Coughlin, Michael W.","first_name":"Michael W."},{"last_name":"Criswell","first_name":"Alexander Wuollet","full_name":"Criswell, Alexander Wuollet"},{"last_name":"Darvish","full_name":"Darvish, Behnam","first_name":"Behnam"},{"last_name":"Das","full_name":"Das, Kaustav K.","first_name":"Kaustav K."},{"first_name":"Kishalay","full_name":"De, Kishalay","last_name":"De"},{"last_name":"Dessart","full_name":"Dessart, Luc","first_name":"Luc"},{"last_name":"Dixon","first_name":"Don","full_name":"Dixon, Don"},{"last_name":"Dorsman","full_name":"Dorsman, Bas","first_name":"Bas"},{"last_name":"Kareem El-Badry","first_name":"Kareem El-Badry","full_name":"Kareem El-Badry, Kareem El-Badry"},{"first_name":"Christopher","full_name":"Evans, Christopher","last_name":"Evans"},{"full_name":"Ford, K. E. Saavik","first_name":"K. E. Saavik","last_name":"Ford"},{"last_name":"Fremling","first_name":"Christoffer","full_name":"Fremling, Christoffer"},{"last_name":"Gansicke","first_name":"Boris T.","full_name":"Gansicke, Boris T."},{"first_name":"Suvi","full_name":"Gezari, Suvi","last_name":"Gezari"},{"id":"d0648d0c-0f64-11ee-a2e0-dd0faa2e4f7d","last_name":"Götberg","first_name":"Ylva Louise Linsdotter","full_name":"Götberg, Ylva Louise Linsdotter","orcid":"0000-0002-6960-6911"},{"last_name":"Green","first_name":"Gregory M.","full_name":"Green, Gregory M."},{"last_name":"Graham","first_name":"Matthew J.","full_name":"Graham, Matthew J."},{"first_name":"Marianne","full_name":"Heida, Marianne","last_name":"Heida"},{"last_name":"Ho","first_name":"Anna Y. Q.","full_name":"Ho, Anna Y. Q."},{"last_name":"Jaodand","full_name":"Jaodand, Amruta D.","first_name":"Amruta D."},{"last_name":"Christopher M. Johns-Krull","full_name":"Christopher M. Johns-Krull, Christopher M. Johns-Krull","first_name":"Christopher M. Johns-Krull"},{"last_name":"Kasliwal","full_name":"Kasliwal, Mansi M.","first_name":"Mansi M."},{"full_name":"Lazzarini, Margaret","first_name":"Margaret","last_name":"Lazzarini"},{"last_name":"Lu","first_name":"Wenbin","full_name":"Lu, Wenbin"},{"first_name":"Raffaella","full_name":"Margutti, Raffaella","last_name":"Margutti"},{"last_name":"Martin","full_name":"Martin, D. Christopher","first_name":"D. Christopher"},{"full_name":"Masters, Daniel Charles","first_name":"Daniel Charles","last_name":"Masters"},{"full_name":"McKernan, Barry","first_name":"Barry","last_name":"McKernan"},{"full_name":"Naze, Yael","first_name":"Yael","last_name":"Naze"},{"full_name":"Nissanke, Samaya M.","first_name":"Samaya M.","last_name":"Nissanke"},{"last_name":"Parazin","first_name":"B.","full_name":"Parazin, B."},{"last_name":"Perley","full_name":"Perley, Daniel A.","first_name":"Daniel A."},{"last_name":"Phinney","full_name":"Phinney, E. Sterl","first_name":"E. Sterl"},{"last_name":"Piro","full_name":"Piro, Anthony L.","first_name":"Anthony L."},{"last_name":"Raaijmakers","first_name":"G.","full_name":"Raaijmakers, G."},{"last_name":"Rauw","full_name":"Rauw, Gregor","first_name":"Gregor"},{"last_name":"Rodriguez","first_name":"Antonio C.","full_name":"Rodriguez, Antonio C."},{"last_name":"Sana","first_name":"Hugues","full_name":"Sana, Hugues"},{"last_name":"Senchyna","first_name":"Peter","full_name":"Senchyna, Peter"},{"last_name":"Singer","full_name":"Singer, Leo P.","first_name":"Leo P."},{"last_name":"Spake","full_name":"Spake, Jessica J.","first_name":"Jessica J."},{"last_name":"Stassun","first_name":"Keivan G.","full_name":"Stassun, Keivan G."},{"last_name":"Stern","full_name":"Stern, Daniel","first_name":"Daniel"},{"last_name":"Teplitz","full_name":"Teplitz, Harry I.","first_name":"Harry I."},{"last_name":"Weisz","full_name":"Weisz, Daniel R.","first_name":"Daniel R."},{"last_name":"Yao","full_name":"Yao, Yuhan","first_name":"Yuhan"}],"date_published":"2021-11-30T00:00:00Z","day":"30","abstract":[{"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.","lang":"eng"}],"publication":"arXiv"},{"keyword":["Electrical and Electronic Engineering"],"publication":"Proceedings of the IEEE","language":[{"iso":"eng"}],"type":"journal_article","department":[{"_id":"FrLo"}],"scopus_import":"1","status":"public","date_updated":"2023-09-11T11:43:35Z","main_file_link":[{"open_access":"1","url":"https://doi.org/10.1109/JPROC.2021.3058954"}],"month":"05","publication_status":"published","volume":109,"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","_id":"14117","page":"612-634","oa_version":"Published Version","quality_controlled":"1","abstract":[{"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.","lang":"eng"}],"day":"01","date_published":"2021-05-01T00:00:00Z","oa":1,"arxiv":1,"author":[{"last_name":"Scholkopf","full_name":"Scholkopf, Bernhard","first_name":"Bernhard"},{"last_name":"Locatello","id":"26cfd52f-2483-11ee-8040-88983bcc06d4","orcid":"0000-0002-4850-0683","first_name":"Francesco","full_name":"Locatello, Francesco"},{"full_name":"Bauer, Stefan","first_name":"Stefan","last_name":"Bauer"},{"full_name":"Ke, Nan Rosemary","first_name":"Nan Rosemary","last_name":"Ke"},{"last_name":"Kalchbrenner","full_name":"Kalchbrenner, Nal","first_name":"Nal"},{"last_name":"Goyal","full_name":"Goyal, Anirudh","first_name":"Anirudh"},{"last_name":"Bengio","full_name":"Bengio, Yoshua","first_name":"Yoshua"}],"article_type":"original","issue":"5","doi":"10.1109/jproc.2021.3058954","title":"Toward causal representation learning","intvolume":"       109","year":"2021","date_created":"2023-08-21T12:19:30Z","publication_identifier":{"eissn":["1558-2256"],"issn":["0018-9219"]},"external_id":{"arxiv":["2102.11107"]},"citation":{"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>","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>.","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.","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.","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>.","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>","short":"B. Scholkopf, F. Locatello, S. Bauer, N.R. Ke, N. Kalchbrenner, A. Goyal, Y. Bengio, Proceedings of the IEEE 109 (2021) 612–634."},"extern":"1","publisher":"Institute of Electrical and Electronics Engineers","article_processing_charge":"No"},{"_id":"14176","page":"11964-11974","oa_version":"Preprint","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","quality_controlled":"1","main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/2106.05142"}],"status":"public","date_updated":"2023-09-11T10:16:55Z","month":"08","publication_status":"published","volume":139,"department":[{"_id":"FrLo"}],"type":"conference","scopus_import":"1","alternative_title":["PMLR"],"publication":"Proceedings of 38th International Conference on Machine Learning","language":[{"iso":"eng"}],"publisher":"ML Research Press","article_processing_charge":"No","extern":"1","citation":{"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.","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.","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.","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.","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.","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."},"title":"Neighborhood contrastive learning applied to online patient monitoring","external_id":{"arxiv":["2106.05142"]},"intvolume":"       139","year":"2021","date_created":"2023-08-22T14:03:04Z","day":"01","conference":{"end_date":"2021-07-24","name":"International Conference on Machine Learning","start_date":"2021-07-18","location":"Virtual"},"abstract":[{"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.","lang":"eng"}],"oa":1,"arxiv":1,"author":[{"full_name":"Yèche, Hugo","first_name":"Hugo","last_name":"Yèche"},{"first_name":"Gideon","full_name":"Dresdner, Gideon","last_name":"Dresdner"},{"orcid":"0000-0002-4850-0683","first_name":"Francesco","full_name":"Locatello, Francesco","last_name":"Locatello","id":"26cfd52f-2483-11ee-8040-88983bcc06d4"},{"full_name":"Hüser, Matthias","first_name":"Matthias","last_name":"Hüser"},{"full_name":"Rätsch, Gunnar","first_name":"Gunnar","last_name":"Rätsch"}],"date_published":"2021-08-01T00:00:00Z"},{"conference":{"name":"ICML: International Conference on Machine Learning","end_date":"2021-07-24","start_date":"2021-07-18","location":"Virtual"},"abstract":[{"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.","lang":"eng"}],"day":"01","date_published":"2021-08-01T00:00:00Z","oa":1,"author":[{"full_name":"Träuble, Frederik","first_name":"Frederik","last_name":"Träuble"},{"last_name":"Creager","full_name":"Creager, Elliot","first_name":"Elliot"},{"last_name":"Kilbertus","first_name":"Niki","full_name":"Kilbertus, Niki"},{"orcid":"0000-0002-4850-0683","full_name":"Locatello, Francesco","first_name":"Francesco","last_name":"Locatello","id":"26cfd52f-2483-11ee-8040-88983bcc06d4"},{"full_name":"Dittadi, Andrea","first_name":"Andrea","last_name":"Dittadi"},{"first_name":"Anirudh","full_name":"Goyal, Anirudh","last_name":"Goyal"},{"last_name":"Schölkopf","full_name":"Schölkopf, Bernhard","first_name":"Bernhard"},{"last_name":"Bauer","full_name":"Bauer, Stefan","first_name":"Stefan"}],"arxiv":1,"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.","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.","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.","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.","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.","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.","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."},"extern":"1","article_processing_charge":"No","publisher":"ML Research Press","title":"On disentangled representations learned from correlated data","intvolume":"       139","date_created":"2023-08-22T14:03:47Z","year":"2021","external_id":{"arxiv":["2006.07886"]},"type":"conference","department":[{"_id":"FrLo"}],"alternative_title":["PMLR"],"scopus_import":"1","publication":"Proceedings of the 38th International Conference on Machine Learning","language":[{"iso":"eng"}],"_id":"14177","oa_version":"Published Version","page":"10401-10412","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","quality_controlled":"1","date_updated":"2023-09-11T10:18:48Z","status":"public","main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/2006.07886"}],"month":"08","volume":139,"publication_status":"published"},{"article_processing_charge":"No","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.","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.","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.","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.","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.","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.","mla":"Dittadi, Andrea, et al. “On the Transfer of Disentangled Representations in Realistic Settings.” <i>The Ninth International Conference on Learning Representations</i>, 2021."},"extern":"1","quality_controlled":"1","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","_id":"14178","oa_version":"Preprint","month":"05","publication_status":"published","external_id":{"arxiv":["2010.14407"]},"year":"2021","date_created":"2023-08-22T14:04:16Z","main_file_link":[{"url":"https://arxiv.org/abs/2010.14407","open_access":"1"}],"title":"On the transfer of disentangled representations in realistic settings","date_updated":"2023-09-11T10:55:30Z","status":"public","department":[{"_id":"FrLo"}],"type":"conference","oa":1,"arxiv":1,"author":[{"first_name":"Andrea","full_name":"Dittadi, Andrea","last_name":"Dittadi"},{"first_name":"Frederik","full_name":"Träuble, Frederik","last_name":"Träuble"},{"full_name":"Locatello, Francesco","first_name":"Francesco","orcid":"0000-0002-4850-0683","id":"26cfd52f-2483-11ee-8040-88983bcc06d4","last_name":"Locatello"},{"full_name":"Wüthrich, Manuel","first_name":"Manuel","last_name":"Wüthrich"},{"first_name":"Vaibhav","full_name":"Agrawal, Vaibhav","last_name":"Agrawal"},{"last_name":"Winther","first_name":"Ole","full_name":"Winther, Ole"},{"last_name":"Bauer","first_name":"Stefan","full_name":"Bauer, Stefan"},{"last_name":"Schölkopf","full_name":"Schölkopf, Bernhard","first_name":"Bernhard"}],"language":[{"iso":"eng"}],"date_published":"2021-05-04T00:00:00Z","day":"04","publication":"The Ninth International Conference on Learning Representations","abstract":[{"lang":"eng","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."}],"conference":{"location":"Virtual","start_date":"2021-05-03","end_date":"2021-05-07","name":"ICLR: International Conference on Learning Representations"}},{"oa":1,"author":[{"first_name":"Julius von","full_name":"Kügelgen, Julius von","last_name":"Kügelgen"},{"last_name":"Sharma","full_name":"Sharma, Yash","first_name":"Yash"},{"full_name":"Gresele, Luigi","first_name":"Luigi","last_name":"Gresele"},{"full_name":"Brendel, Wieland","first_name":"Wieland","last_name":"Brendel"},{"last_name":"Schölkopf","first_name":"Bernhard","full_name":"Schölkopf, Bernhard"},{"full_name":"Besserve, Michel","first_name":"Michel","last_name":"Besserve"},{"id":"26cfd52f-2483-11ee-8040-88983bcc06d4","last_name":"Locatello","full_name":"Locatello, Francesco","first_name":"Francesco","orcid":"0000-0002-4850-0683"}],"arxiv":1,"date_published":"2021-06-08T00:00:00Z","day":"08","conference":{"name":"NeurIPS: Neural Information Processing Systems","end_date":"2021-12-10","location":"Virtual","start_date":"2021-12-07"},"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"}],"article_processing_charge":"No","citation":{"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.","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.","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.","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.","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.","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.","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."},"extern":"1","publication_identifier":{"isbn":["9781713845393"]},"external_id":{"arxiv":["2106.04619"]},"intvolume":"        34","date_created":"2023-08-22T14:04:36Z","year":"2021","title":"Self-supervised learning with data augmentations provably isolates content from style","department":[{"_id":"FrLo"}],"type":"conference","language":[{"iso":"eng"}],"publication":"Advances in Neural Information Processing Systems","quality_controlled":"1","oa_version":"Preprint","_id":"14179","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","page":"16451-16467","publication_status":"published","month":"06","volume":34,"main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/2106.04619"}],"status":"public","date_updated":"2023-09-11T10:33:19Z"},{"intvolume":"        34","date_created":"2023-08-22T14:04:55Z","year":"2021","publication_identifier":{"isbn":["9781713845393"]},"external_id":{"arxiv":["2110.06399"]},"title":"Dynamic inference with neural interpreters","citation":{"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.","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.","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.","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.","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.","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."},"extern":"1","article_processing_charge":"No","date_published":"2021-10-12T00:00:00Z","oa":1,"author":[{"last_name":"Rahaman","first_name":"Nasim","full_name":"Rahaman, Nasim"},{"first_name":"Muhammad Waleed","full_name":"Gondal, Muhammad Waleed","last_name":"Gondal"},{"full_name":"Joshi, Shruti","first_name":"Shruti","last_name":"Joshi"},{"full_name":"Gehler, Peter","first_name":"Peter","last_name":"Gehler"},{"full_name":"Bengio, Yoshua","first_name":"Yoshua","last_name":"Bengio"},{"id":"26cfd52f-2483-11ee-8040-88983bcc06d4","last_name":"Locatello","first_name":"Francesco","full_name":"Locatello, Francesco","orcid":"0000-0002-4850-0683"},{"last_name":"Schölkopf","first_name":"Bernhard","full_name":"Schölkopf, Bernhard"}],"arxiv":1,"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. "}],"conference":{"start_date":"2021-12-07","location":"Virtual","end_date":"2021-12-10","name":"NeurIPS: Neural Information Processing Systems"},"day":"12","month":"10","volume":34,"publication_status":"published","status":"public","date_updated":"2024-10-14T12:27:25Z","main_file_link":[{"url":"https://doi.org/10.48550/arXiv.2110.06399","open_access":"1"}],"quality_controlled":"1","oa_version":"Preprint","_id":"14180","page":"10985-10998","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","language":[{"iso":"eng"}],"publication":"Advances in Neural Information Processing Systems","type":"conference","department":[{"_id":"FrLo"}]},{"type":"conference","department":[{"_id":"FrLo"}],"language":[{"iso":"eng"}],"publication":"Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence","quality_controlled":"1","page":"2337-2343","_id":"14181","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","oa_version":"Published Version","publication_status":"published","month":"05","date_updated":"2023-09-11T11:14:30Z","status":"public","main_file_link":[{"url":"https://doi.org/10.48550/arXiv.2105.09240","open_access":"1"}],"doi":"10.24963/ijcai.2021/322","date_published":"2021-05-19T00:00:00Z","arxiv":1,"author":[{"first_name":"Gideon","full_name":"Dresdner, Gideon","last_name":"Dresdner"},{"full_name":"Shekhar, Saurav","first_name":"Saurav","last_name":"Shekhar"},{"full_name":"Pedregosa, Fabian","first_name":"Fabian","last_name":"Pedregosa"},{"orcid":"0000-0002-4850-0683","full_name":"Locatello, Francesco","first_name":"Francesco","last_name":"Locatello","id":"26cfd52f-2483-11ee-8040-88983bcc06d4"},{"full_name":"Rätsch, Gunnar","first_name":"Gunnar","last_name":"Rätsch"}],"oa":1,"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."}],"conference":{"location":"Montreal, Canada","start_date":"2021-08-19","end_date":"2021-08-27","name":"IJCAI: International Joint Conference on Artificial Intelligence"},"day":"19","extern":"1","citation":{"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.","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.","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>.","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.","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>","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>."},"article_processing_charge":"No","publisher":"International Joint Conferences on Artificial Intelligence","date_created":"2023-08-22T14:05:14Z","year":"2021","external_id":{"arxiv":["2105.09240"]},"publication_identifier":{"eisbn":["9780999241196"]},"title":"Boosting variational inference with locally adaptive step-sizes"},{"department":[{"_id":"FrLo"}],"type":"conference","language":[{"iso":"eng"}],"publication":"35th Conference on Neural Information Processing Systems","quality_controlled":"1","page":"116-128","_id":"14182","oa_version":"Preprint","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","month":"07","publication_status":"published","volume":34,"main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/2107.01057"}],"status":"public","date_updated":"2023-09-11T11:31:59Z","oa":1,"author":[{"last_name":"Träuble","first_name":"Frederik","full_name":"Träuble, Frederik"},{"last_name":"Kügelgen","first_name":"Julius von","full_name":"Kügelgen, Julius von"},{"full_name":"Kleindessner, Matthäus","first_name":"Matthäus","last_name":"Kleindessner"},{"last_name":"Locatello","id":"26cfd52f-2483-11ee-8040-88983bcc06d4","orcid":"0000-0002-4850-0683","full_name":"Locatello, Francesco","first_name":"Francesco"},{"last_name":"Schölkopf","full_name":"Schölkopf, Bernhard","first_name":"Bernhard"},{"first_name":"Peter","full_name":"Gehler, Peter","last_name":"Gehler"}],"arxiv":1,"date_published":"2021-07-02T00:00:00Z","day":"02","conference":{"name":"NeurIPS: Neural Information Processing Systems","end_date":"2021-12-10","start_date":"2021-12-07","location":"Virtual"},"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"}],"article_processing_charge":"No","extern":"1","citation":{"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.","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.","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.","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.","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.","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.","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."},"publication_identifier":{"isbn":["9781713845393"]},"external_id":{"arxiv":["2107.01057"]},"intvolume":"        34","year":"2021","date_created":"2023-08-22T14:05:41Z","title":"Backward-compatible prediction updates: A probabilistic approach"},{"main_file_link":[{"open_access":"1","url":"https://patents.google.com/patent/US20210383199A1/en"}],"date_updated":"2025-01-31T11:35:46Z","status":"public","title":"Object-centric learning with slot attention","external_id":{"arxiv":["2006.15055"]},"month":"12","date_created":"2023-08-22T14:07:06Z","year":"2021","_id":"14185","oa_version":"Published Version","user_id":"8b945eb4-e2f2-11eb-945a-df72226e66a9","application_date":"2020-07-13","article_processing_charge":"No","ipn":"US20210383199A1","citation":{"ista":"Weissenborn D, Uszkoreit J, Unterthiner T, Mahendran A, Locatello F, Kipf T, Heigold G, Dosovitskiy A. 2021. Object-centric learning with slot attention.","ieee":"D. Weissenborn <i>et al.</i>, “Object-centric learning with slot attention.” 2021.","chicago":"Weissenborn, Dirk, Jakob Uszkoreit, Thomas Unterthiner, Aravindh Mahendran, Francesco Locatello, Thomas Kipf, Georg Heigold, and Alexey Dosovitskiy. “Object-Centric Learning with Slot Attention,” 2021.","apa":"Weissenborn, D., Uszkoreit, J., Unterthiner, T., Mahendran, A., Locatello, F., Kipf, T., … Dosovitskiy, A. (2021). Object-centric learning with slot attention.","short":"D. Weissenborn, J. Uszkoreit, T. Unterthiner, A. Mahendran, F. Locatello, T. Kipf, G. Heigold, A. Dosovitskiy, (2021).","ama":"Weissenborn D, Uszkoreit J, Unterthiner T, et al. Object-centric learning with slot attention. 2021.","mla":"Weissenborn, Dirk, et al. <i>Object-Centric Learning with Slot Attention</i>. 2021."},"extern":"1","day":"09","ipc":"G06N 3/063 ; G06N 3/08 ; G06F 17/16","abstract":[{"text":"A method involves receiving a perceptual representation including a plurality of feature vectors, and initializing a plurality of slot vectors represented by a neural network memory unit. Each respective slot vector is configured to represent a corresponding entity in the perceptual representation. The method also involves determining an attention matrix based on a product of the plurality of feature vectors transformed by a key function and the plurality of slot vectors transformed by a query function. Each respective value of a plurality of values along each respective dimension of the attention matrix is normalized with respect to the plurality of values. The method additionally involves determining an update matrix based on the plurality of feature vectors transformed by a value function and the attention matrix, and updating the plurality of slot vectors based on the update matrix by way of the neural network memory unit.","lang":"eng"}],"arxiv":1,"author":[{"first_name":"Dirk","full_name":"Weissenborn, Dirk","last_name":"Weissenborn"},{"last_name":"Uszkoreit","first_name":"Jakob","full_name":"Uszkoreit, Jakob"},{"last_name":"Unterthiner","first_name":"Thomas","full_name":"Unterthiner, Thomas"},{"first_name":"Aravindh","full_name":"Mahendran, Aravindh","last_name":"Mahendran"},{"full_name":"Locatello, Francesco","first_name":"Francesco","orcid":"0000-0002-4850-0683","id":"26cfd52f-2483-11ee-8040-88983bcc06d4","last_name":"Locatello"},{"first_name":"Thomas","full_name":"Kipf, Thomas","last_name":"Kipf"},{"full_name":"Heigold, Georg","first_name":"Georg","last_name":"Heigold"},{"full_name":"Dosovitskiy, Alexey","first_name":"Alexey","last_name":"Dosovitskiy"}],"oa":1,"applicant":["Google LLC"],"date_published":"2021-12-09T00:00:00Z","department":[{"_id":"FrLo"}],"application_number":"16 / 927,018 ","type":"patent","OA_place":"repository","publication_date":"2021-12-09"},{"main_file_link":[{"url":"https://doi.org/10.48550/arXiv.2111.13693","open_access":"1"}],"date_updated":"2024-10-14T12:27:49Z","status":"public","title":"Enforcing and discovering structure in machine learning","external_id":{"arxiv":["2111.13693"]},"publication_status":"submitted","month":"11","date_created":"2023-08-22T14:23:35Z","year":"2021","oa_version":"Preprint","_id":"14221","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","article_processing_charge":"No","article_number":"2111.13693","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>.","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>","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>","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>.","ieee":"F. Locatello, “Enforcing and discovering structure in machine learning,” <i>arXiv</i>. .","ista":"Locatello F. Enforcing and discovering structure in machine learning. arXiv, 2111.13693."},"extern":"1","day":"26","publication":"arXiv","abstract":[{"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.","lang":"eng"}],"author":[{"first_name":"Francesco","full_name":"Locatello, Francesco","orcid":"0000-0002-4850-0683","id":"26cfd52f-2483-11ee-8040-88983bcc06d4","last_name":"Locatello"}],"arxiv":1,"language":[{"iso":"eng"}],"oa":1,"date_published":"2021-11-26T00:00:00Z","department":[{"_id":"FrLo"}],"type":"preprint","doi":"10.48550/arXiv.2111.13693"},{"day":"23","publication":"ICML 2021 Workshop on Unsupervised Reinforcement Learning","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."}],"conference":{"location":"Virtual","start_date":"2021-07-23","end_date":"2021-07-23","name":"ICML: International Conference on Machine Learning"},"author":[{"full_name":"Träuble, Frederik","first_name":"Frederik","last_name":"Träuble"},{"last_name":"Dittadi","first_name":"Andrea","full_name":"Dittadi, Andrea"},{"full_name":"Wuthrich, Manuel","first_name":"Manuel","last_name":"Wuthrich"},{"full_name":"Widmaier, Felix","first_name":"Felix","last_name":"Widmaier"},{"full_name":"Gehler, Peter Vincent","first_name":"Peter Vincent","last_name":"Gehler"},{"first_name":"Ole","full_name":"Winther, Ole","last_name":"Winther"},{"first_name":"Francesco","full_name":"Locatello, Francesco","orcid":"0000-0002-4850-0683","id":"26cfd52f-2483-11ee-8040-88983bcc06d4","last_name":"Locatello"},{"full_name":"Bachem, Olivier","first_name":"Olivier","last_name":"Bachem"},{"first_name":"Bernhard","full_name":"Schölkopf, Bernhard","last_name":"Schölkopf"},{"full_name":"Bauer, Stefan","first_name":"Stefan","last_name":"Bauer"}],"language":[{"iso":"eng"}],"date_published":"2021-07-23T00:00:00Z","department":[{"_id":"FrLo"}],"type":"conference","title":"Representation learning for out-of-distribution generalization in reinforcement learning","date_updated":"2023-09-13T12:44:00Z","status":"public","publication_status":"published","month":"07","year":"2021","date_created":"2023-09-13T12:43:14Z","oa_version":"None","_id":"14332","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","article_processing_charge":"No","citation":{"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.","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.","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.","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.","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.","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."},"extern":"1","quality_controlled":"1"},{"_id":"14800","oa_version":"Submitted Version","user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","article_number":"2108017","quality_controlled":"1","main_file_link":[{"open_access":"1","url":"https://doi.org/10.3866/PKU.WHXB202108017"}],"date_updated":"2025-09-10T10:12:25Z","status":"public","isi":1,"month":"10","volume":37,"publication_status":"published","department":[{"_id":"MaIb"}],"type":"journal_article","scopus_import":"1","publication":"Acta Physico-Chimica Sinica","language":[{"iso":"eng"}],"publisher":"Peking University","article_processing_charge":"No","citation":{"short":"C. Chang, W. Chen, Y. Chen, Y. Chen, Y. Chen, F. Ding, C. Fan, H.J. Fan, Z. Fan, C. Gong, Y. Gong, Q. He, X. Hong, S. Hu, W. Hu, W. Huang, Y. Huang, W. Ji, D. Li, L.J. Li, Q. Li, L. Lin, C. Ling, M. Liu, N. Liu, Z. Liu, K.P. Loh, J. Ma, F. Miao, H. Peng, M. Shao, L. Song, S. Su, S. Sun, C. Tan, Z. Tang, D. Wang, H. Wang, J. Wang, X. Wang, X. Wang, A.T.S. Wee, Z. Wei, Y. Wu, Z.S. Wu, J. Xiong, Q. Xiong, W. Xu, P. Yin, H. Zeng, Z. Zeng, T. Zhai, H. Zhang, H. Zhang, Q. Zhang, T. Zhang, X. Zhang, L.D. Zhao, M. Zhao, W. Zhao, Y. Zhao, K.G. Zhou, X. Zhou, Y. Zhou, H. Zhu, H. Zhang, Z. Liu, Acta Physico-Chimica Sinica 37 (2021).","mla":"Chang, Cheng, et al. “Recent Progress on Two-Dimensional Materials.” <i>Acta Physico-Chimica Sinica</i>, vol. 37, no. 12, 2108017, Peking University, 2021, doi:<a href=\"https://doi.org/10.3866/PKU.WHXB202108017\">10.3866/PKU.WHXB202108017</a>.","ama":"Chang C, Chen W, Chen Y, et al. Recent progress on two-dimensional materials. <i>Acta Physico-Chimica Sinica</i>. 2021;37(12). doi:<a href=\"https://doi.org/10.3866/PKU.WHXB202108017\">10.3866/PKU.WHXB202108017</a>","ieee":"C. Chang <i>et al.</i>, “Recent progress on two-dimensional materials,” <i>Acta Physico-Chimica Sinica</i>, vol. 37, no. 12. Peking University, 2021.","ista":"Chang C, Chen W, Chen Y, Chen Y, Chen Y, Ding F, Fan C, Fan HJ, Fan Z, Gong C, Gong Y, He Q, Hong X, Hu S, Hu W, Huang W, Huang Y, Ji W, Li D, Li LJ, Li Q, Lin L, Ling C, Liu M, Liu N, Liu Z, Loh KP, Ma J, Miao F, Peng H, Shao M, Song L, Su S, Sun S, Tan C, Tang Z, Wang D, Wang H, Wang J, Wang X, Wang X, Wee ATS, Wei Z, Wu Y, Wu ZS, Xiong J, Xiong Q, Xu W, Yin P, Zeng H, Zeng Z, Zhai T, Zhang H, Zhang H, Zhang Q, Zhang T, Zhang X, Zhao LD, Zhao M, Zhao W, Zhao Y, Zhou KG, Zhou X, Zhou Y, Zhu H, Zhang H, Liu Z. 2021. Recent progress on two-dimensional materials. Acta Physico-Chimica Sinica. 37(12), 2108017.","chicago":"Chang, Cheng, Wei Chen, Ye Chen, Yonghua Chen, Yu Chen, Feng Ding, Chunhai Fan, et al. “Recent Progress on Two-Dimensional Materials.” <i>Acta Physico-Chimica Sinica</i>. Peking University, 2021. <a href=\"https://doi.org/10.3866/PKU.WHXB202108017\">https://doi.org/10.3866/PKU.WHXB202108017</a>.","apa":"Chang, C., Chen, W., Chen, Y., Chen, Y., Chen, Y., Ding, F., … Liu, Z. (2021). Recent progress on two-dimensional materials. <i>Acta Physico-Chimica Sinica</i>. Peking University. <a href=\"https://doi.org/10.3866/PKU.WHXB202108017\">https://doi.org/10.3866/PKU.WHXB202108017</a>"},"title":"Recent progress on two-dimensional materials","external_id":{"isi":["000731879300002"]},"publication_identifier":{"issn":["1001-4861"]},"year":"2021","date_created":"2024-01-14T23:00:58Z","intvolume":"        37","issue":"12","article_type":"review","doi":"10.3866/PKU.WHXB202108017","day":"13","abstract":[{"lang":"eng","text":"Research on two-dimensional (2D) materials has been explosively increasing in last seventeen years in varying subjects including condensed matter physics, electronic engineering, materials science, and chemistry since the mechanical exfoliation of graphene in 2004. Starting from graphene, 2D materials now have become a big family with numerous members and diverse categories. The unique structural features and physicochemical properties of 2D materials make them one class of the most appealing candidates for a wide range of potential applications. In particular, we have seen some major breakthroughs made in the field of 2D materials in last five years not only in developing novel synthetic methods and exploring new structures/properties but also in identifying innovative applications and pushing forward commercialisation. In this review, we provide a critical summary on the recent progress made in the field of 2D materials with a particular focus on last five years. After a brief background introduction, we first discuss the major synthetic methods for 2D materials, including the mechanical exfoliation, liquid exfoliation, vapor phase deposition, and wet-chemical synthesis as well as phase engineering of 2D materials belonging to the field of phase engineering of nanomaterials (PEN). We then introduce the superconducting/optical/magnetic properties and chirality of 2D materials along with newly emerging magic angle 2D superlattices. Following that, the promising applications of 2D materials in electronics, optoelectronics, catalysis, energy storage, solar cells, biomedicine, sensors, environments, etc. are described sequentially. Thereafter, we present the theoretic calculations and simulations of 2D materials. Finally, after concluding the current progress, we provide some personal discussions on the existing challenges and future outlooks in this rapidly developing field. "}],"author":[{"id":"9E331C2E-9F27-11E9-AE48-5033E6697425","last_name":"Chang","full_name":"Chang, Cheng","first_name":"Cheng","orcid":"0000-0002-9515-4277"},{"last_name":"Chen","first_name":"Wei","full_name":"Chen, Wei"},{"last_name":"Chen","first_name":"Ye","full_name":"Chen, Ye"},{"last_name":"Chen","full_name":"Chen, Yonghua","first_name":"Yonghua"},{"first_name":"Yu","full_name":"Chen, Yu","last_name":"Chen"},{"first_name":"Feng","full_name":"Ding, Feng","last_name":"Ding"},{"last_name":"Fan","first_name":"Chunhai","full_name":"Fan, Chunhai"},{"first_name":"Hong Jin","full_name":"Fan, Hong Jin","last_name":"Fan"},{"last_name":"Fan","first_name":"Zhanxi","full_name":"Fan, Zhanxi"},{"first_name":"Cheng","full_name":"Gong, Cheng","last_name":"Gong"},{"last_name":"Gong","first_name":"Yongji","full_name":"Gong, Yongji"},{"full_name":"He, Qiyuan","first_name":"Qiyuan","last_name":"He"},{"last_name":"Hong","first_name":"Xun","full_name":"Hong, Xun"},{"first_name":"Sheng","full_name":"Hu, Sheng","last_name":"Hu"},{"last_name":"Hu","full_name":"Hu, Weida","first_name":"Weida"},{"last_name":"Huang","full_name":"Huang, Wei","first_name":"Wei"},{"first_name":"Yuan","full_name":"Huang, Yuan","last_name":"Huang"},{"last_name":"Ji","first_name":"Wei","full_name":"Ji, Wei"},{"last_name":"Li","first_name":"Dehui","full_name":"Li, Dehui"},{"last_name":"Li","full_name":"Li, Lain Jong","first_name":"Lain Jong"},{"last_name":"Li","full_name":"Li, Qiang","first_name":"Qiang"},{"first_name":"Li","full_name":"Lin, Li","last_name":"Lin"},{"last_name":"Ling","first_name":"Chongyi","full_name":"Ling, Chongyi"},{"last_name":"Liu","full_name":"Liu, Minghua","first_name":"Minghua"},{"last_name":"Liu","full_name":"Liu, Nan","first_name":"Nan"},{"full_name":"Liu, Zhuang","first_name":"Zhuang","last_name":"Liu"},{"full_name":"Loh, Kian Ping","first_name":"Kian Ping","last_name":"Loh"},{"last_name":"Ma","first_name":"Jianmin","full_name":"Ma, Jianmin"},{"first_name":"Feng","full_name":"Miao, Feng","last_name":"Miao"},{"last_name":"Peng","full_name":"Peng, Hailin","first_name":"Hailin"},{"last_name":"Shao","first_name":"Mingfei","full_name":"Shao, Mingfei"},{"last_name":"Song","first_name":"Li","full_name":"Song, Li"},{"last_name":"Su","first_name":"Shao","full_name":"Su, Shao"},{"first_name":"Shuo","full_name":"Sun, Shuo","last_name":"Sun"},{"full_name":"Tan, Chaoliang","first_name":"Chaoliang","last_name":"Tan"},{"last_name":"Tang","first_name":"Zhiyong","full_name":"Tang, Zhiyong"},{"first_name":"Dingsheng","full_name":"Wang, Dingsheng","last_name":"Wang"},{"last_name":"Wang","first_name":"Huan","full_name":"Wang, Huan"},{"first_name":"Jinlan","full_name":"Wang, Jinlan","last_name":"Wang"},{"full_name":"Wang, Xin","first_name":"Xin","last_name":"Wang"},{"last_name":"Wang","full_name":"Wang, Xinran","first_name":"Xinran"},{"last_name":"Wee","full_name":"Wee, Andrew T.S.","first_name":"Andrew T.S."},{"full_name":"Wei, Zhongming","first_name":"Zhongming","last_name":"Wei"},{"first_name":"Yuen","full_name":"Wu, Yuen","last_name":"Wu"},{"first_name":"Zhong Shuai","full_name":"Wu, Zhong Shuai","last_name":"Wu"},{"last_name":"Xiong","full_name":"Xiong, Jie","first_name":"Jie"},{"full_name":"Xiong, Qihua","first_name":"Qihua","last_name":"Xiong"},{"last_name":"Xu","full_name":"Xu, Weigao","first_name":"Weigao"},{"full_name":"Yin, Peng","first_name":"Peng","last_name":"Yin"},{"first_name":"Haibo","full_name":"Zeng, Haibo","last_name":"Zeng"},{"full_name":"Zeng, Zhiyuan","first_name":"Zhiyuan","last_name":"Zeng"},{"first_name":"Tianyou","full_name":"Zhai, Tianyou","last_name":"Zhai"},{"full_name":"Zhang, Han","first_name":"Han","last_name":"Zhang"},{"last_name":"Zhang","first_name":"Hui","full_name":"Zhang, Hui"},{"full_name":"Zhang, Qichun","first_name":"Qichun","last_name":"Zhang"},{"full_name":"Zhang, Tierui","first_name":"Tierui","last_name":"Zhang"},{"full_name":"Zhang, Xiang","first_name":"Xiang","last_name":"Zhang"},{"first_name":"Li Dong","full_name":"Zhao, Li Dong","last_name":"Zhao"},{"last_name":"Zhao","first_name":"Meiting","full_name":"Zhao, Meiting"},{"full_name":"Zhao, Weijie","first_name":"Weijie","last_name":"Zhao"},{"full_name":"Zhao, Yunxuan","first_name":"Yunxuan","last_name":"Zhao"},{"first_name":"Kai Ge","full_name":"Zhou, Kai Ge","last_name":"Zhou"},{"last_name":"Zhou","full_name":"Zhou, Xing","first_name":"Xing"},{"full_name":"Zhou, Yu","first_name":"Yu","last_name":"Zhou"},{"first_name":"Hongwei","full_name":"Zhu, Hongwei","last_name":"Zhu"},{"last_name":"Zhang","full_name":"Zhang, Hua","first_name":"Hua"},{"first_name":"Zhongfan","full_name":"Liu, Zhongfan","last_name":"Liu"}],"oa":1,"date_published":"2021-10-13T00:00:00Z"},{"type":"journal_article","department":[{"_id":"RoSe"}],"ec_funded":1,"corr_author":"1","scopus_import":"1","publication":"Pure and Applied Analysis","project":[{"call_identifier":"H2020","grant_number":"754411","_id":"260C2330-B435-11E9-9278-68D0E5697425","name":"ISTplus - Postdoctoral Fellowships"},{"name":"Analysis of quantum many-body systems","_id":"25C6DC12-B435-11E9-9278-68D0E5697425","call_identifier":"H2020","grant_number":"694227"}],"language":[{"iso":"eng"}],"page":"653-676","_id":"14889","oa_version":"Preprint","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","quality_controlled":"1","date_updated":"2025-04-14T07:27:00Z","status":"public","main_file_link":[{"url":"https://doi.org/10.48550/arXiv.2005.02098","open_access":"1"}],"volume":3,"publication_status":"published","month":"10","article_type":"original","issue":"4","acknowledgement":"Financial support by the European Union’s Horizon 2020 research and innovation programme\r\nunder the Marie Skłodowska-Curie grant agreement No. 754411 (S.R.) and the European\r\nResearch Council under grant agreement No. 694227 (N.L. and R.S.), as well as by the SNSF\r\nEccellenza project PCEFP2 181153 (N.L.), the NCCR SwissMAP (N.L. and B.S.) and by the\r\nDeutsche Forschungsgemeinschaft (DFG) through the Research Training Group 1838: Spectral\r\nTheory and Dynamics of Quantum Systems (D.M.) is gratefully acknowledged. B.S. gratefully\r\nacknowledges financial support from the Swiss National Science Foundation through the Grant\r\n“Dynamical and energetic properties of Bose-Einstein condensates” and from the European\r\nResearch Council through the ERC-AdG CLaQS (grant agreement No 834782). D.M. thanks\r\nMarcel Griesemer for helpful discussions.","doi":"10.2140/paa.2021.3.653","abstract":[{"text":"We consider the Fröhlich Hamiltonian with large coupling constant α. For initial data of Pekar product form with coherent phonon field and with the electron minimizing the corresponding energy, we provide a norm approximation of the evolution, valid up to times of order α2. The approximation is given in terms of a Pekar product state, evolved through the Landau-Pekar equations, corrected by a Bogoliubov dynamics taking quantum fluctuations into account. This allows us to show that the Landau-Pekar equations approximately describe the evolution of the electron- and one-phonon reduced density matrices under the Fröhlich dynamics up to times of order α2.","lang":"eng"}],"day":"01","date_published":"2021-10-01T00:00:00Z","oa":1,"author":[{"id":"4BC40BEC-F248-11E8-B48F-1D18A9856A87","last_name":"Leopold","full_name":"Leopold, Nikolai K","first_name":"Nikolai K","orcid":"0000-0002-0495-6822"},{"first_name":"David Johannes","full_name":"Mitrouskas, David Johannes","last_name":"Mitrouskas","id":"cbddacee-2b11-11eb-a02e-a2e14d04e52d"},{"orcid":"0000-0001-5059-4466","full_name":"Rademacher, Simone Anna Elvira","first_name":"Simone Anna Elvira","last_name":"Rademacher","id":"856966FE-A408-11E9-977E-802DE6697425"},{"full_name":"Schlein, Benjamin","first_name":"Benjamin","last_name":"Schlein"},{"full_name":"Seiringer, Robert","first_name":"Robert","orcid":"0000-0002-6781-0521","id":"4AFD0470-F248-11E8-B48F-1D18A9856A87","last_name":"Seiringer"}],"arxiv":1,"citation":{"apa":"Leopold, N. K., Mitrouskas, D. J., Rademacher, S. A. E., Schlein, B., &#38; Seiringer, R. (2021). Landau–Pekar equations and quantum fluctuations for the dynamics of a strongly coupled polaron. <i>Pure and Applied Analysis</i>. Mathematical Sciences Publishers. <a href=\"https://doi.org/10.2140/paa.2021.3.653\">https://doi.org/10.2140/paa.2021.3.653</a>","chicago":"Leopold, Nikolai K, David Johannes Mitrouskas, Simone Anna Elvira Rademacher, Benjamin Schlein, and Robert Seiringer. “Landau–Pekar Equations and Quantum Fluctuations for the Dynamics of a Strongly Coupled Polaron.” <i>Pure and Applied Analysis</i>. Mathematical Sciences Publishers, 2021. <a href=\"https://doi.org/10.2140/paa.2021.3.653\">https://doi.org/10.2140/paa.2021.3.653</a>.","ista":"Leopold NK, Mitrouskas DJ, Rademacher SAE, Schlein B, Seiringer R. 2021. Landau–Pekar equations and quantum fluctuations for the dynamics of a strongly coupled polaron. Pure and Applied Analysis. 3(4), 653–676.","ieee":"N. K. Leopold, D. J. Mitrouskas, S. A. E. Rademacher, B. Schlein, and R. Seiringer, “Landau–Pekar equations and quantum fluctuations for the dynamics of a strongly coupled polaron,” <i>Pure and Applied Analysis</i>, vol. 3, no. 4. Mathematical Sciences Publishers, pp. 653–676, 2021.","mla":"Leopold, Nikolai K., et al. “Landau–Pekar Equations and Quantum Fluctuations for the Dynamics of a Strongly Coupled Polaron.” <i>Pure and Applied Analysis</i>, vol. 3, no. 4, Mathematical Sciences Publishers, 2021, pp. 653–76, doi:<a href=\"https://doi.org/10.2140/paa.2021.3.653\">10.2140/paa.2021.3.653</a>.","ama":"Leopold NK, Mitrouskas DJ, Rademacher SAE, Schlein B, Seiringer R. Landau–Pekar equations and quantum fluctuations for the dynamics of a strongly coupled polaron. <i>Pure and Applied Analysis</i>. 2021;3(4):653-676. doi:<a href=\"https://doi.org/10.2140/paa.2021.3.653\">10.2140/paa.2021.3.653</a>","short":"N.K. Leopold, D.J. Mitrouskas, S.A.E. Rademacher, B. Schlein, R. Seiringer, Pure and Applied Analysis 3 (2021) 653–676."},"article_processing_charge":"No","publisher":"Mathematical Sciences Publishers","title":"Landau–Pekar equations and quantum fluctuations for the dynamics of a strongly coupled polaron","intvolume":"         3","year":"2021","date_created":"2024-01-28T23:01:43Z","publication_identifier":{"issn":["2578-5893"],"eissn":["2578-5885"]},"external_id":{"arxiv":["2005.02098"]}},{"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","_id":"14890","page":"677-726","oa_version":"Preprint","quality_controlled":"1","status":"public","date_updated":"2025-04-14T07:44:02Z","main_file_link":[{"url":"https://doi.org/10.48550/arXiv.1912.11004","open_access":"1"}],"month":"10","publication_status":"published","volume":3,"type":"journal_article","department":[{"_id":"RoSe"}],"ec_funded":1,"scopus_import":"1","corr_author":"1","publication":"Pure and Applied Analysis","project":[{"grant_number":"754411","call_identifier":"H2020","_id":"260C2330-B435-11E9-9278-68D0E5697425","name":"ISTplus - Postdoctoral Fellowships"}],"language":[{"iso":"eng"}],"citation":{"short":"L. Bossmann, S.P. Petrat, P. Pickl, A. Soffer, Pure and Applied Analysis 3 (2021) 677–726.","ama":"Bossmann L, Petrat SP, Pickl P, Soffer A. Beyond Bogoliubov dynamics. <i>Pure and Applied Analysis</i>. 2021;3(4):677-726. doi:<a href=\"https://doi.org/10.2140/paa.2021.3.677\">10.2140/paa.2021.3.677</a>","mla":"Bossmann, Lea, et al. “Beyond Bogoliubov Dynamics.” <i>Pure and Applied Analysis</i>, vol. 3, no. 4, Mathematical Sciences Publishers, 2021, pp. 677–726, doi:<a href=\"https://doi.org/10.2140/paa.2021.3.677\">10.2140/paa.2021.3.677</a>.","ieee":"L. Bossmann, S. P. Petrat, P. Pickl, and A. Soffer, “Beyond Bogoliubov dynamics,” <i>Pure and Applied Analysis</i>, vol. 3, no. 4. Mathematical Sciences Publishers, pp. 677–726, 2021.","ista":"Bossmann L, Petrat SP, Pickl P, Soffer A. 2021. Beyond Bogoliubov dynamics. Pure and Applied Analysis. 3(4), 677–726.","chicago":"Bossmann, Lea, Sören P Petrat, Peter Pickl, and Avy Soffer. “Beyond Bogoliubov Dynamics.” <i>Pure and Applied Analysis</i>. Mathematical Sciences Publishers, 2021. <a href=\"https://doi.org/10.2140/paa.2021.3.677\">https://doi.org/10.2140/paa.2021.3.677</a>.","apa":"Bossmann, L., Petrat, S. P., Pickl, P., &#38; Soffer, A. (2021). Beyond Bogoliubov dynamics. <i>Pure and Applied Analysis</i>. Mathematical Sciences Publishers. <a href=\"https://doi.org/10.2140/paa.2021.3.677\">https://doi.org/10.2140/paa.2021.3.677</a>"},"article_processing_charge":"No","publisher":"Mathematical Sciences Publishers","title":"Beyond Bogoliubov dynamics","intvolume":"         3","year":"2021","date_created":"2024-01-28T23:01:43Z","publication_identifier":{"eissn":["2578-5885"],"issn":["2578-5893"]},"external_id":{"arxiv":["1912.11004"]},"article_type":"original","issue":"4","acknowledgement":"We are grateful for the hospitality of Central China Normal University (CCNU),\r\nwhere parts of this work were done, and thank Phan Th`anh Nam, Simone\r\nRademacher, Robert Seiringer and Stefan Teufel for helpful discussions. L.B. gratefully acknowledges the support by the German Research Foundation (DFG) within the Research\r\nTraining Group 1838 “Spectral Theory and Dynamics of Quantum Systems”, and the funding\r\nfrom the European Union’s Horizon 2020 research and innovation programme under the Marie\r\nSk lodowska-Curie Grant Agreement No. 754411.","doi":"10.2140/paa.2021.3.677","abstract":[{"text":"We consider a system of N interacting bosons in the mean-field scaling regime and construct corrections to the Bogoliubov dynamics that approximate the true N-body dynamics in norm to arbitrary precision. The N-independent corrections are given in terms of the solutions of the Bogoliubov and Hartree equations and satisfy a generalized form of Wick's theorem. We determine the n-point correlation functions of the excitations around the condensate, as well as the reduced densities of the N-body system, to arbitrary accuracy, given only the knowledge of the two-point functions of a quasi-free state and the solution of the Hartree equation. In this way, the complex problem of computing all n-point correlation functions for an interacting N-body system is essentially reduced to the problem of solving the Hartree equation and the PDEs for the Bogoliubov two-point functions.","lang":"eng"}],"day":"01","date_published":"2021-10-01T00:00:00Z","oa":1,"author":[{"id":"A2E3BCBE-5FCC-11E9-AA4B-76F3E5697425","last_name":"Bossmann","first_name":"Lea","full_name":"Bossmann, Lea","orcid":"0000-0002-6854-1343"},{"last_name":"Petrat","id":"40AC02DC-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-9166-5889","full_name":"Petrat, Sören P","first_name":"Sören P"},{"full_name":"Pickl, Peter","first_name":"Peter","last_name":"Pickl"},{"full_name":"Soffer, Avy","first_name":"Avy","last_name":"Soffer"}],"arxiv":1},{"day":"28","publication":"Encyclopedia of Life Sciences","abstract":[{"text":"Hybrid zones are narrow geographic regions where different populations, races or interbreeding species meet and mate, producing mixed ‘hybrid’ offspring. They are relatively common and can be found in a diverse range of organisms and environments. The study of hybrid zones has played an important role in our understanding of the origin of species, with hybrid zones having been described as ‘natural laboratories’. This is because they allow us to study,in situ, the conditions and evolutionary forces that enable divergent taxa to remain distinct despite some ongoing gene exchange between them.","lang":"eng"}],"language":[{"iso":"eng"}],"author":[{"full_name":"Stankowski, Sean","first_name":"Sean","id":"43161670-5719-11EA-8025-FABC3DDC885E","last_name":"Stankowski"},{"orcid":"0000-0002-1145-9226","full_name":"Shipilina, Daria","first_name":"Daria","last_name":"Shipilina","id":"428A94B0-F248-11E8-B48F-1D18A9856A87"},{"orcid":"0000-0003-1050-4969","first_name":"Anja M","full_name":"Westram, Anja M","last_name":"Westram","id":"3C147470-F248-11E8-B48F-1D18A9856A87"}],"date_published":"2021-05-28T00:00:00Z","series_title":"eLS","department":[{"_id":"NiBa"}],"type":"book_chapter","corr_author":"1","doi":"10.1002/9780470015902.a0029355","status":"public","date_updated":"2024-10-09T21:08:11Z","title":"Hybrid Zones","publication_status":"published","publication_identifier":{"eisbn":["9780470015902"],"isbn":["9780470016176"]},"volume":2,"month":"05","year":"2021","date_created":"2024-02-14T12:05:50Z","intvolume":"         2","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","_id":"14984","oa_version":"None","article_processing_charge":"No","publisher":"Wiley","quality_controlled":"1","citation":{"apa":"Stankowski, S., Shipilina, D., &#38; Westram, A. M. (2021). Hybrid Zones. In <i>Encyclopedia of Life Sciences</i> (Vol. 2). Wiley. <a href=\"https://doi.org/10.1002/9780470015902.a0029355\">https://doi.org/10.1002/9780470015902.a0029355</a>","chicago":"Stankowski, Sean, Daria Shipilina, and Anja M Westram. “Hybrid Zones.” In <i>Encyclopedia of Life Sciences</i>, Vol. 2. ELS. Wiley, 2021. <a href=\"https://doi.org/10.1002/9780470015902.a0029355\">https://doi.org/10.1002/9780470015902.a0029355</a>.","ista":"Stankowski S, Shipilina D, Westram AM. 2021.Hybrid Zones. In: Encyclopedia of Life Sciences. vol. 2.","ieee":"S. Stankowski, D. Shipilina, and A. M. Westram, “Hybrid Zones,” in <i>Encyclopedia of Life Sciences</i>, vol. 2, Wiley, 2021.","ama":"Stankowski S, Shipilina D, Westram AM. Hybrid Zones. In: <i>Encyclopedia of Life Sciences</i>. Vol 2. eLS. Wiley; 2021. doi:<a href=\"https://doi.org/10.1002/9780470015902.a0029355\">10.1002/9780470015902.a0029355</a>","mla":"Stankowski, Sean, et al. “Hybrid Zones.” <i>Encyclopedia of Life Sciences</i>, vol. 2, Wiley, 2021, doi:<a href=\"https://doi.org/10.1002/9780470015902.a0029355\">10.1002/9780470015902.a0029355</a>.","short":"S. Stankowski, D. Shipilina, A.M. Westram, in:, Encyclopedia of Life Sciences, Wiley, 2021."}}]