Lechner, M., Zikelic, D., Chatterjee, K., Henzinger, T. A., &; Rus, D. (2023). Quantization-aware interval bound propagation for training certifiably robust quantized neural networks. In Proceedings of the 37th AAAI Conference on Artificial Intelligence (Vol. 37, pp. 14964–14973). Washington, DC, United States: Association for the Advancement of Artificial Intelligence.https://doi.org/10.1609/aaai.v37i12.26747 

Avni, G., Jecker, I. R., &; Zikelic, D. (2023). Bidding graph games with partially-observable budgets. In Proceedings of the 37th AAAI Conference on Artificial Intelligence (Vol. 37, pp. 5464–5471). Washington, DC, United States.https://doi.org/10.1609/aaai.v37i5.25679 

Tojo, K., Shamir, A., Bickel, B., &; Umetani, N. (2023). Stealth shaper: Reflectivity optimization as surface stylization. In SIGGRAPH 2023 Conference Proceedings. Los Angeles, CA, United States: Association for Computing Machinery.https://doi.org/10.1145/3588432.3591542 

Ladle, D. R., &; Hippenmeyer, S. (2023). Loss of ET/E in motor neurons leads to reduced monosynaptic inputs from proprioceptive sensory neurons. Journal of Neurophysiology. American Physiological Society.https://doi.org/10.1152/jn.00172.2022 

Henzinger, T. A., Karimi, M., Kueffner, K., &; Mallik, K. (2023). Monitoring algorithmic fairness. In Computer Aided Verification (Vol. 13965, pp. 358–382). Paris, France: Springer Nature.https://doi.org/10.1007/978-3-031-37703-7_17 

Glajzer, J., Castillo-Tong, D. C., Richter, R., Vergote, I., Kulbe, H., Vanderstichele, A.,https://doi.org/10.1245/s10434-022-12459-3__Braicu, E. I. (2023). Impact of BRCA mutation status on tumor dissemination pattern, surgical outcome and patient survival in primary and recurrent high-grade serous ovarian cancer: A multicenter retrospective study by the Ovarian Cancer Therapy-Innovative Models Prolong Survival (OCTIPS) consortium. Annals of Surgical Oncology. Springer Nature.https://doi.org/10.1245/s10434-022-12459-3 

Glajzer, J., Castillo-Tong, D. C., Richter, R., Vergote, I., Kulbe, H., Vanderstichele, A.,https://doi.org/10.1245/s10434-022-12681-z__Braicu, E. I. (2023). ASO Visual Abstract: Impact of BRCA mutation status on tumor dissemination pattern, surgical outcome, and patient survival in primary and recurrent high-grade serous ovarian cancer (HGSOC). A multicenter, retrospective study of the ovarian cancer therapy—innovative models prolong survival (OCTIPS) consortium. Annals of Surgical Oncology. Springer Nature.https://doi.org/10.1245/s10434-022-12681-z 

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.