Usable Information and Evolution of Optimal Representations During Training. - Michael Kleinman; Alessandro Achille; Daksh Idnani; Jonathan C. Kao (ICLR, 2021)

A mechanistic multi-area recurrent network model of decision-making. - Michael Kleinman; Chandramouli Chandrasekaran; Jonathan C. Kao (NeurIPS, 2021)

Learning rule influences recurrent network representations but not attractor structure in decision-making tasks. - Brandon McMahan; Michael Kleinman; Jonathan C. Kao (NeurIPS, 2021)

Redundant Information Neural Estimation. - Michael Kleinman; Alessandro Achille; Stefano Soatto; Jonathan C. Kao (Entropy, 2021)

Critical Learning Periods for Multisensory Integration in Deep Networks. - Michael Kleinman; Alessandro Achille; Stefano Soatto (CVPR, 2023)

Gacs-Korner Common Information Variational Autoencoder. - Michael Kleinman; Alessandro Achille; Stefano Soatto; Jonathan C. Kao (NeurIPS, 2023)

On the Structure and Learning of Perceptual Representations in Deep Neural Networks - Michael Kleinman (2023)

Critical Learning Periods Emerge Even in Deep Linear Networks. - Michael Kleinman; Alessandro Achille; Stefano Soatto (ICLR, 2024)

Voice EHR: Introducing Multimodal Audio Data for Health. - James T. Anibal; Hannah Huth; Ming Li 052; Lindsey Hazen; Yen Minh Lam; Nguyen Thi Thu Hang; Michael Kleinman; Shelley Ost; Christopher Jackson; Laura Sprabery; Cheran Elangovan; Balaji Krishnaiah; et al. (CoRR, 2024)

Towards a theory of learning dynamics in deep state space models. - Jakub Smékal; Jimmy T. H. Smith; Michael Kleinman; Dan Biderman; Scott W. Linderman (CoRR, 2024)

Voice EHR: introducing multimodal audio data for health. - James T. Anibal; Hannah Huth; Ming Li 052; Lindsey Hazen; Veronica Daoud; Dominique Ebedes; Yen Minh Lam; Hang Nguyen; Phuc Vo Hong; Michael Kleinman; Shelley Ost; Christopher Jackson; et al. (Frontiers Digit. Health, 2024)