Reverse-engineering recurrent neural network solutions to a hierarchical inference task for mice. - Rylan Schaeffer; Mikail Khona; Leenoy Meshulam; International Brain Laboratory; Ila Fiete (NeurIPS, 2020)

Deep Graph Pose: a semi-supervised deep graphical model for improved animal pose tracking. - Anqi Wu; Estefany Kelly Buchanan; Matthew R. Whiteway; Michael Schartner; Guido Meijer; Jean-Paul Noel; Erica Rodriguez; Claire Everett; Amy Norovich; Evan Schaffer; Neeli Mishra; C. Daniel Salzman; et al. (NeurIPS, 2020)

Exploring learning trajectories with dynamic infinite hidden Markov models. - Sebastian A. Bruijns; International Brain Laboratory; Peter Dayan (CogSci, 2021)

Decentralized Motion Inference and Registration of Neuropixel Data. - Erdem Varol; Julien Boussard; Nishchal Dethe; Olivier Winter; Anne E. Urai; International Brain Laboratory; Anne Churchland; Nick Steinmetz; Liam Paninski (ICASSP, 2021)

Partitioning variability in animal behavioral videos using semi-supervised variational autoencoders. - Matthew R. Whiteway; Dan Biderman; Yoni Friedman; Mario Dipoppa; Estefany Kelly Buchanan; Anqi Wu; John Zhou; Niccolò Bonacchi; Nathaniel J. Miska; Jean-Paul Noel; Erica Rodriguez; Michael Schartner; et al. (PLoS Comput. Biol., 2021)

Parsing neural dynamics with infinite recurrent switching linear dynamical systems. - Victor Geadah; International Brain Laboratory; Jonathan W. Pillow (ICLR, 2024)

Towards a "Universal Translator" for Neural Dynamics at Single-Cell, Single-Spike Resolution. - Yizi Zhang; Yanchen Wang; Donato Jiménez-Benetó; Zixuan Wang; Mehdi Azabou; Blake A. Richards; Renee Tung; Olivier Winter; International Brain Laboratory; Eva L. Dyer; Liam Paninski; Cole L. Hurwitz (NeurIPS, 2024)

Towards a "universal translator" for neural dynamics at single-cell, single-spike resolution. - Yizi Zhang; Yanchen Wang; Donato Jiménez-Benetó; Zixuan Wang; Mehdi Azabou; Blake A. Richards; Olivier Winter; International Brain Laboratory; Eva L. Dyer; Liam Paninski; Cole L. Hurwitz (CoRR, 2024)

A study of animal action segmentation algorithms across supervised, unsupervised, and semi-supervised learning paradigms. - Ari Blau; Evan S. Schaffer; Neeli Mishra; Nathaniel J. Miska; International Brain Laboratory; Liam Paninski; Matthew R. Whiteway (CoRR, 2024)

In vivo cell-type and brain region classification via multimodal contrastive learning. - Han Yu; Hanrui Lyu; YiXun Xu; Charlie Windolf; Eric Kenji Lee; Fan Yang; Andrew M. Shelton; Olivier Winter; International Brain Laboratory; Eva L. Dyer; Chandramouli Chandrasekaran; Nicholas A. Steinmetz; et al. (ICLR, 2025)

Neural Encoding and Decoding at Scale. - Yizi Zhang; Yanchen Wang; Mehdi Azabou; Alexandre Andre; Zixuan Wang; Hanrui Lyu; International Brain Laboratory; Eva L. Dyer; Liam Paninski; Cole L. Hurwitz (CoRR, 2025)

Self-supervised pretraining of vision transformers for animal behavioral analysis and neural encoding. - Yanchen Wang; Han Yu; Ari Blau; Yizi Zhang; International Brain Laboratory; Liam Paninski; Cole L. Hurwitz; Matthew R. Whiteway (CoRR, 2025)