Drop, Swap, and Generate: A Self-Supervised Approach for Generating Neural Activity. - Ran Liu; Mehdi Azabou; Max Dabagia; Chi-Heng Lin; Mohammad Gheshlaghi Azar; Keith B. Hengen; Michal Valko; Eva L. Dyer (NeurIPS, 2021)

Mine Your Own vieW: Self-Supervised Learning Through Across-Sample Prediction. - Mehdi Azabou; Mohammad Gheshlaghi Azar; Ran Liu; Chi-Heng Lin; Erik C. Johnson; Kiran Bhaskaran-Nair; Max Dabagia; Keith B. Hengen; William R. Gray Roncal; Michal Valko; Eva L. Dyer (CoRR, 2021)

Learning Sinkhorn divergences for supervised change point detection. - Nauman Ahad; Eva L. Dyer; Keith B. Hengen; Yao Xie; Mark A. Davenport (CoRR, 2022)

IoT cloud laboratory: Internet of Things architecture for cellular biology. - David F. Parks; Kateryna Voitiuk; Jinghui Geng; Matthew A. T. Elliott; Matthew G. Keefe; Erik A. Jung; Ash Robbins; Pierre V. Baudin; Victoria T. Ly; Nico Hawthorne; Dylan Yong; Sebastian E. Sanso; et al. (Internet Things, 2022)

Detecting change points in neural population activity with contrastive metric learning. - Carolina Urzay; Nauman Ahad; Mehdi Azabou; Aidan Schneider; Geethika Atamkuri; Keith B. Hengen; Eva L. Dyer (NER, 2023)