Barbier J, Camilli F, Mondelli M, Sáenz M. Fundamental limits in structured principal component analysis and how to reach them. Proceedings of the National Academy of Sciences of the United States of America. 2023;120(30). doi:10.1073/pnas.2302028120

Vardi O, Maroudas-Sklare N, Kolodny Y, et al. Nuclear spin effects in biological processes. Proceedings of the National Academy of Sciences of the United States of America. 2023;120(32). doi:10.1073/pnas.2300828120

Dubach G, Erdös L. Dynamics of a rank-one perturbation of a Hermitian matrix. Electronic Communications in Probability. 2023;28:1-13. doi:10.1214/23-ECP516

Cipolloni G, Erdös L, Schröder DJ. Functional central limit theorems for Wigner matrices. Annals of Applied Probability. 2023;33(1):447-489. doi:10.1214/22-AAP1820

Browning TD, Boudec PL, Sawin W. The Hasse principle for random Fano hypersurfaces. Annals of Mathematics. 2023;197(3):1115-1203. doi:10.4007/annals.2023.197.3.3

Mckerral JC, Kleshnina M, Ejov V, Bartle L, Mitchell JG, Filar JA. Empirical parameterisation and dynamical analysis of the allometric Rosenzweig-MacArthur equations. PLoS One. 2023;18(2):e0279838. doi:10.1371/journal.pone.0279838

Eguchi K, Le Monnier E, Shigemoto R. Nanoscale phosphoinositide distribution on cell membranes of mouse cerebellar neurons. The Journal of Neuroscience. 2023;43(23):4197-4216. doi:10.1523/JNEUROSCI.1514-22.2023

Bonolis D, Browning TD. Uniform bounds for rational points on hyperelliptic fibrations. Annali della Scuola Normale Superiore di Pisa - Classe di Scienze. 2023;24(1):173-204. doi:10.2422/2036-2145.202010_018

Confavreux BJ. Synapseek: Meta-learning synaptic plasticity rules. 2023. doi:10.15479/at:ista:14422

Roos B. Boundary superconductivity in BCS theory. 2023. doi:10.15479/at:ista:14374

Hainzl C, Roos B, Seiringer R. Boundary superconductivity in the BCS model. Journal of Spectral Theory. 2023;12(4):1507–1540. doi:10.4171/JST/439

Barton NH, Etheridge AM, Véber A. The infinitesimal model with dominance. Genetics. 2023;225(2). doi:10.1093/genetics/iyad133

Barton NH. The infinitesimal model with dominance. 2023. doi:10.15479/AT:ISTA:12949

Markov I, Vladu A, Guo Q, Alistarh D-A. Quantized distributed training of large models with convergence guarantees. In: Proceedings of the 40th International Conference on Machine Learning. Vol 202. ML Research Press; 2023:24020-24044.

Fichtenberger H, Henzinger MH, Upadhyay J. Constant matters: Fine-grained error bound on differentially private continual observation. In: Proceedings of the 40th International Conference on Machine Learning. Vol 202. ML Research Press; 2023:10072-10092.

Shevchenko A, Kögler K, Hassani H, Mondelli M. Fundamental limits of two-layer autoencoders, and achieving them with gradient methods. In: Proceedings of the 40th International Conference on Machine Learning. Vol 202. ML Research Press; 2023:31151-31209.

Nikdan M, Pegolotti T, Iofinova EB, Kurtic E, Alistarh D-A. SparseProp: Efficient sparse backpropagation for faster training of neural networks at the edge. In: Proceedings of the 40th International Conference on Machine Learning. Vol 202. ML Research Press; 2023:26215-26227.

Hoffmann C, Simkin M. Stronger lower bounds for leakage-resilient secret sharing. In: 8th International Conference on Cryptology and Information Security in Latin America. Vol 14168. Springer Nature; 2023:215-228. doi:10.1007/978-3-031-44469-2_11

Frantar E, Alistarh D-A. SparseGPT: Massive language models can be accurately pruned in one-shot. In: Proceedings of the 40th International Conference on Machine Learning. Vol 202. ML Research Press; 2023:10323-10337.

Cornalba F, Disselkamp C, Scassola D, Helf C. Multi-objective reward generalization: improving performance of Deep Reinforcement Learning for applications in single-asset trading. Neural Computing and Applications. 2023. doi:10.1007/s00521-023-09033-7