Neighborhood contrastive learning applied to online patient monitoring
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.

On disentangled representations learned from correlated data
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.

On the transfer of disentangled representations in realistic settings
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.

Self-supervised learning with data augmentations provably isolates content from style
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.

Dynamic inference with neural interpreters
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.

Boosting variational inference with locally adaptive step-sizes
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.

Backward-compatible prediction updates: A probabilistic approach
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.

Enforcing and discovering structure in machine learning
F. Locatello, ArXiv (n.d.).

Representation learning for out-of-distribution generalization in reinforcement learning
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.

Loss of Hem1 disrupts macrophage function and impacts migration, phagocytosis, and integrin-mediated adhesion
S. Stahnke, H. Döring, C. Kusch, D.J.J. de Gorter, S. Dütting, A. Guledani, I. Pleines, M. Schnoor, M.K. Sixt, R. Geffers, M. Rohde, M. Müsken, F. Kage, A. Steffen, J. Faix, B. Nieswandt, K. Rottner, T.E.B. Stradal, Current Biology 31 (2021) 2051–2064.e8.

PIPEcloned human IgE and Ig antibodies: New tools for investigating cow's milk allergy and tolerance
C.L. Pranger, J. Singer, V.K. Köhler, I. PaliSchöll, A. Fiocchi, S.N. Karagiannis, O. Zenarruzabeitia, F. Borrego, E. JensenJarolim, Allergy 76 (2021) 1553–1556.

Using replicate hybrid zones to understand the genomic basis of adaptive divergence
A.M. Westram, R. Faria, K. Johannesson, R. Butlin, Molecular Ecology 30 (2021) 3797–3814.

A scalable concurrent algorithm for dynamic connectivity
A. Fedorov, N. Koval, D.-A. Alistarh, in:, Proceedings of the 33rd ACM Symposium on Parallelism in Algorithms and Architectures, Association for Computing Machinery, 2021, pp. 208–220.

On the volume of sections of the cube
G. Ivanov, I. Tsiutsiurupa, Analysis and Geometry in Metric Spaces 9 (2021) 1–18.

Tight frames and related geometric problems
G. Ivanov, Canadian Mathematical Bulletin 64 (2021) 942–963.

The San Diego Nathan Shock Center: Tackling the heterogeneity of aging
G.S. Shadel, P.D. Adams, W.T. Berggren, J.K. Diedrich, K.E. Diffenderfer, F.H. Gage, N. Hah, M. Hansen, M. Hetzer, A.J.A. Molina, U. Manor, K. Marek, D.D. O’Keefe, A.F.M. Pinto, A. Sacco, T.O. Sharpee, M.N. Shokriev, S. Zambetti, GeroScience 43 (2021) 2139–2148.

Recovery and analysis of rest-frame UV emission lines in 2052 galaxies observed with MUSE at 1.5 < z < 6.4
K.B. Schmidt, J. Kerutt, L. Wisotzki, T. Urrutia, A. Feltre, M.V. Maseda, T. Nanayakkara, R. Bacon, L.A. Boogaard, S. Conseil, T. Contini, E.C. Herenz, W. Kollatschny, M. Krumpe, F. Leclercq, G. Mahler, J.J. Matthee, V. Mauerhofer, J. Richard, J. Schaye, Astronomy &; Astrophysics 654 (2021).

The MUSE Extremely Deep Field: The cosmic web in emission at high redshift
R. Bacon, D. Mary, T. Garel, J. Blaizot, M. Maseda, J. Schaye, L. Wisotzki, S. Conseil, J. Brinchmann, F. Leclercq, V. Abril-Melgarejo, L. Boogaard, N.F. Bouché, T. Contini, A. Feltre, B. Guiderdoni, C. Herenz, W. Kollatschny, H. Kusakabe, J.J. Matthee, L. Michel-Dansac, T. Nanayakkara, J. Richard, M. Roth, K.B. Schmidt, M. Steinmetz, L. Tresse, T. Urrutia, A. Verhamme, P.M. Weilbacher, J. Zabl, S.L. Zoutendijk, Astronomy &; Astrophysics 647 (2021).

Measuring the average molecular gas content of star-forming galaxies at z = 3–4
L.A. Boogaard, R.J. Bouwens, D. Riechers, P. van der Werf, R. Bacon, J.J. Matthee, M. Stefanon, A. Feltre, M. Maseda, H. Inami, M. Aravena, J. Brinchmann, C. Carilli, T. Contini, R. Decarli, J. González-López, T. Nanayakkara, F. Walter, The Astrophysical Journal 916 (2021).

Lyman-;1 transmission properties of the intergalactic medium in the CoDaII simulation
M. Gronke, P. Ocvirk, C. Mason, J.J. Matthee, S.E.I. Bosman, J.G. Sorce, J. Lewis, K. Ahn, D. Aubert, T. Dawoodbhoy, I.T. Iliev, P.R. Shapiro, G. Yepes, Monthly Notices of the Royal Astronomical Society 508 (2021) 3697–3709.