Vierra, N. C., Ribeiro-Silva, L., Kirmiz, M., Van Der List, D., Bhandari, P., Mack, O. A.,https://doi.org/10.1038/s41467-023-40930-6__Trimmer, J. S. (2023). Neuronal ER-plasma membrane junctions couple excitation to C+-activated PKA signaling. Nature Communications. Springer Nature.https://doi.org/10.1038/s41467-023-40930-6 

Kretinsky, J., Meggendorfer, T., Prokop, M., &; Rieder, S. (2023). Guessing winning policies in LTL synthesis by semantic learning. In 35th International Conference on Computer Aided Verification  (Vol. 13964, pp. 390–414). Paris, France: Springer Nature.https://doi.org/10.1007/978-3-031-37706-8_20 

Sinha, S., Gehler, P., Locatello, F., &; Schiele, B. (2023). TeST: Test-time Self-Training under distribution shift. In 2023 IEEE/CVF Winter Conference on Applications of Computer Vision. Waikoloa, HI, United States: Institute of Electrical and Electronics Engineers.https://doi.org/10.1109/wacv56688.2023.00278 

Mathis, S., &; Bugnet, L. A. (2023). Asymmetries of frequency splittings of dipolar mixed modes: A window on the topology of deep magnetic fields. Astronomy and Astrophysics. EDP Sciences.https://doi.org/10.1051/0004-6361/202346832 

Gamper, J., Kluibenschedl, F., Weiss, A. K. H., &; Hofer, T. S. (2023). Accessing position space wave functions in band structure calculations of periodic systems - a generalized, adapted numerov implementation for one-, two-, and three-dimensional quantum problems. Journal of Physical Chemistry Letters. American Chemical Society.https://doi.org/10.1021/acs.jpclett.3c01707 

Zhu, Z., Liu, F., Chrysos, G. G., Locatello, F., &; Cevher, V. (2023). Benign overfitting in deep neural networks under lazy training. In Proceedings of the 40th International Conference on Machine Learning (Vol. 202, pp. 43105–43128). Honolulu, Hawaii, United States: ML Research Press.

Burg, M. F., Wenzel, F., Zietlow, D., Horn, M., Makansi, O., Locatello, F., &; Russell, C. (n.d.). A data augmentation perspective on diffusion models and retrieval. arXiv.https://doi.org/10.48550/arXiv.2304.10253 

Montagna, F., Noceti, N., Rosasco, L., Zhang, K., &; Locatello, F. (2023). Causal discovery with score matching on additive models with arbitrary noise. In 2nd Conference on Causal Learning and Reasoning. Tübingen, Germany.

Montagna, F., Noceti, N., Rosasco, L., Zhang, K., &; Locatello, F. (2023). Scalable causal discovery with score matching. In 2nd Conference on Causal Learning and Reasoning. Tübingen, Germany.

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

Moschella, L., Maiorca, V., Fumero, M., Norelli, A., Locatello, F., &; Rodolà, E. (2023). Relative representations enable zero-shot latent space communication. In The 11th International Conference on Learning Representations. Kigali, Rwanda.

Tangemann, M., Schneider, S., Kügelgen, J. von, Locatello, F., Gehler, P., Brox, T.,  Schölkopf, B. (2023). Unsupervised object learning via common fate. In 2nd Conference on Causal Learning and Reasoning. Tübingen, Germany.

Seitzer, M., Horn, M., Zadaianchuk, A., Zietlow, D., Xiao, T., Carl-Johann Simon-Gabriel, C.-J. S.-G.,  Locatello, F. (2023). Bridging the gap to real-world object-centric learning. In The 11th International Conference on Learning Representations. Kigali, Rwanda.

Zadaianchuk, A., Kleindessner, M., Zhu, Y., Locatello, F., &; Brox, T. (2023). Unsupervised semantic segmentation with self-supervised object-centric representations. In The 11th International Conference on Learning Representations. Kigali, Rwanda.

Faller, P. M., Vankadara, L. C., Mastakouri, A. A., Locatello, F., &; Janzing, D. (n.d.). Self-compatibility: Evaluating causal discovery without ground truth. arXiv.https://doi.org/10.48550/arXiv.2307.09552 

Boocock, D. R., Hirashima, T., &; Hannezo, E. B. (2023). Interplay between mechanochemical patterning and glassy dynamics in cellular monolayers. PRX Life. American Physical Society.https://doi.org/10.1103/prxlife.1.013001 

Nardin, M., Käfer, K., Stella, F., &; Csicsvari, J. L. (2023). Theta oscillations as a substrate for medial prefrontal-hippocampal assembly interactions. Cell Reports. Elsevier.https://doi.org/10.1016/j.celrep.2023.113015 

Cho, U. H., &; Hetzer, M. (2023). Caspase-mediated nuclear pore complex trimming in cell differentiation and endoplasmic reticulum stress. ELife. eLife Sciences Publications.https://doi.org/10.7554/eLife.89066 

Anastos, M., Fabian, D., Müyesser, A., &; Szabó, T. (2023). Splitting matchings and the Ryser-Brualdi-Stein conjecture for multisets. Electronic Journal of Combinatorics. Electronic Journal of Combinatorics.https://doi.org/10.37236/11714 

Sun, Y., Fu, H., Chatterjee, K., &; Goharshady, A. K. (2023). Automated tail bound analysis for probabilistic recurrence relations. In Computer Aided Verification (Vol. 13966, pp. 16–39). Paris, France: Springer Nature.https://doi.org/10.1007/978-3-031-37709-9_2