Neuronal ER-plasma membrane junctions couple excitation to C+-activated PKA signaling
N.C. Vierra, L. Ribeiro-Silva, M. Kirmiz, D. Van Der List, P. Bhandari, O.A. Mack, J. Carroll, E. Le Monnier, S.A. Aicher, R. Shigemoto, J.S. Trimmer, Nature Communications 14 (2023).

Guessing winning policies in LTL synthesis by semantic learning
J. Kretinsky, T. Meggendorfer, M. Prokop, S. Rieder, in:, 35th International Conference on Computer Aided Verification , Springer Nature, 2023, pp. 390–414.

TeST: Test-time Self-Training under distribution shift
S. Sinha, P. Gehler, F. Locatello, B. Schiele, in:, 2023 IEEE/CVF Winter Conference on Applications of Computer Vision, Institute of Electrical and Electronics Engineers, 2023.

Asymmetries of frequency splittings of dipolar mixed modes: A window on the topology of deep magnetic fields
S. Mathis, L.A. Bugnet, Astronomy and Astrophysics 676 (2023).

Benign overfitting in deep neural networks under lazy training
Z. Zhu, F. Liu, G.G. Chrysos, F. Locatello, V. Cevher, in:, Proceedings of the 40th International Conference on Machine Learning, ML Research Press, 2023, pp. 43105–43128.

A data augmentation perspective on diffusion models and retrieval
M.F. Burg, F. Wenzel, D. Zietlow, M. Horn, O. Makansi, F. Locatello, C. Russell, ArXiv (n.d.).

Causal discovery with score matching on additive models with arbitrary noise
F. Montagna, N. Noceti, L. Rosasco, K. Zhang, F. Locatello, in:, 2nd Conference on Causal Learning and Reasoning, 2023.

Scalable causal discovery with score matching
F. Montagna, N. Noceti, L. Rosasco, K. Zhang, F. Locatello, in:, 2nd Conference on Causal Learning and Reasoning, 2023.

Causal triplet: An open challenge for intervention-centric causal representation learning
Y. Liu, A. Alahi, C. Russell, M. Horn, D. Zietlow, B. Schölkopf, F. Locatello, in:, 2nd Conference on Causal Learning and Reasoning, 2023.

Relative representations enable zero-shot latent space communication
L. Moschella, V. Maiorca, M. Fumero, A. Norelli, F. Locatello, E. Rodolà, in:, The 11th International Conference on Learning Representations, 2023.

Unsupervised object learning via common fate
M. Tangemann, S. Schneider, J. von Kügelgen, F. Locatello, P. Gehler, T. Brox, M. Kümmerer, M. Bethge, B. Schölkopf, in:, 2nd Conference on Causal Learning and Reasoning, 2023.

Bridging the gap to real-world object-centric learning
M. Seitzer, M. Horn, A. Zadaianchuk, D. Zietlow, T. Xiao, C.-J.S.-G. Carl-Johann Simon-Gabriel, T. He, Z. Zhang, B. Schölkopf, T. Brox, F. Locatello, in:, The 11th International Conference on Learning Representations, 2023.

Unsupervised semantic segmentation with self-supervised object-centric representations
A. Zadaianchuk, M. Kleindessner, Y. Zhu, F. Locatello, T. Brox, in:, The 11th International Conference on Learning Representations, 2023.

Self-compatibility: Evaluating causal discovery without ground truth
P.M. Faller, L.C. Vankadara, A.A. Mastakouri, F. Locatello, D. Janzing, ArXiv (n.d.).

Interplay between mechanochemical patterning and glassy dynamics in cellular monolayers
D.R. Boocock, T. Hirashima, E.B. Hannezo, PRX Life 1 (2023).

Theta oscillations as a substrate for medial prefrontal-hippocampal assembly interactions
M. Nardin, K. Käfer, F. Stella, J.L. Csicsvari, Cell Reports 42 (2023).

Caspase-mediated nuclear pore complex trimming in cell differentiation and endoplasmic reticulum stress
U.H. Cho, M. Hetzer, ELife 12 (2023).

Splitting matchings and the Ryser-Brualdi-Stein conjecture for multisets
M. Anastos, D. Fabian, A. Müyesser, T. Szabó, Electronic Journal of Combinatorics 30 (2023).

Automated tail bound analysis for probabilistic recurrence relations
Y. Sun, H. Fu, K. Chatterjee, A.K. Goharshady, in:, Computer Aided Verification, Springer Nature, 2023, pp. 16–39.

MDPs as distribution transformers: Affine invariant synthesis for safety objectives
S. Akshay, K. Chatterjee, T. Meggendorfer, D. Zikelic, in:, International Conference on Computer Aided Verification, Springer Nature, 2023, pp. 86–112.