A latent variable modeling framework for analyzing neural population activity. - Matthew R. Whiteway (2018)

BehaveNet: nonlinear embedding and Bayesian neural decoding of behavioral videos. - Eleanor Batty; Matthew R. Whiteway; Shreya Saxena; Dan Biderman; Taiga Abe; Simon Musall; Winthrop Gillis; Jeffrey E. Markowitz; Anne Churchland; John P. Cunningham; Sandeep R. Datta; Scott W. Linderman; et al. (NeurIPS, 2019)

Recurrent Switching Dynamical Systems Models for Multiple Interacting Neural Populations. - Joshua I. Glaser; Matthew R. Whiteway; John P. Cunningham; Liam Paninski; Scott W. Linderman (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)

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)

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)

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)