Bridging the Gap: Point Clouds for Merging Neurons in Connectomics. - Jules Berman; Dmitri B. Chklovskii; Jingpeng Wu (MIDL, 2022)

Representational Dissimilarity Metric Spaces for Stochastic Neural Networks. - Lyndon R. Duong; Jingyang Zhou; Josue Nassar; Jules Berman; Jeroen Olieslagers; Alex H. Williams (ICLR, 2023)

Randomized Sparse Neural Galerkin Schemes for Solving Evolution Equations with Deep Networks. - Jules Berman; Benjamin Peherstorfer (NeurIPS, 2023)

CoLoRA: Continuous low-rank adaptation for reduced implicit neural modeling of parameterized partial differential equations. - Jules Berman; Benjamin Peherstorfer (ICML, 2024)

Parametric model reduction of mean-field and stochastic systems via higher-order action matching. - Jules Berman; Tobias Blickhan; Benjamin Peherstorfer (NeurIPS, 2024)

Neuronal Temporal Filters as Normal Mode Extractors. - Siavash Golkar; Jules Berman; David Lipshutz; Robert Mihai Haret; Tim Gollisch; Dmitri B. Chklovskii (CoRR, 2024)

Nonlinear Embeddings for Conserving Hamiltonians and Other Quantities with Neural Galerkin Schemes. - Paul Schwerdtner; Philipp Schulze; Jules Berman; Benjamin Peherstorfer (SIAM J. Sci. Comput., 2024)

DICE: Discrete inverse continuity equation for learning population dynamics. - Tobias Blickhan; Jules Berman; Andrew Stuart; Benjamin Peherstorfer (CoRR, 2025)