Michael Kleinman

19 papers A* 6Journal 12

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Experience-Guided Adaptation of Inference-Time Reasoning Strategies. CoRR Adam Stein, Matthew Trager, Benjamin Bowman, Michael Kleinman, Aditya Chattopadhyay, Wei Xia, Stefano Soatto
2025	J	`jnl`	LATTS: Locally Adaptive Test-Time Scaling. CoRR Theo Uscidda, Matthew Trager, Michael Kleinman, Aditya Chattopadhyay, Wei Xia, Stefano Soatto
2025	J	`jnl`	Re-FORC: Adaptive Reward Prediction for Efficient Chain-of-Thought Reasoning. CoRR Renos Zabounidis, Aditya Golatkar, Michael Kleinman, Alessandro Achille, Wei Xia, Stefano Soatto
2025	J	`jnl`	e1: Learning Adaptive Control of Reasoning Effort. CoRR Michael Kleinman, Matthew Trager, Alessandro Achille, Wei Xia, Stefano Soatto
2024	A*	`conf`	Critical Learning Periods Emerge Even in Deep Linear Networks. ICLR Michael Kleinman, Alessandro Achille, Stefano Soatto
2024	J	`jnl`	Towards a theory of learning dynamics in deep state space models. CoRR Jakub Smékal, Jimmy T. H. Smith, Michael Kleinman, Dan Biderman, Scott W. Linderman
2024	J	`jnl`	Voice EHR: Introducing Multimodal Audio Data for Health. CoRR James T. Anibal, Hannah Huth, Ming Li, Lindsey Hazen, Yen Minh Lam, Nguyen Thi Thu Hang, Michael Kleinman, Shelley Ost, Christopher Jackson, Laura Sprabery, Cheran Elangovan, Balaji Krishnaiah, Lee Akst, Ioan Lina, Iqbal Elyazar, Lenny Ekwati, Stefan Jansen, Richard Nduwayezu, Charisse Garcia, Jeffrey Plum, Jacqueline Brenner, Miranda Song, Emily Ricotta, David A. Clifton, Louise Thwaites, Yael Bensoussan, Bradford J. Wood
2024	J	`jnl`	Voice EHR: introducing multimodal audio data for health. Frontiers Digit. Health James T. Anibal, Hannah Huth, Ming Li, Lindsey Hazen, Veronica Daoud, Dominique Ebedes, Yen Minh Lam, Hang Nguyen, Phuc Vo Hong, Michael Kleinman, Shelley Ost, Christopher Jackson, Laura Sprabery, Cheran Elangovan, Balaji Krishnaiah, Lee Akst, Ioan Lina, Iqbal Elyazar, Lenny Ekawati, Stefan Jansen, Richard Nduwayezu, Charisse Garcia, Jeffrey Plum, Jacqueline Brenner, Miranda Song, Emily Ricotta, David A. Clifton, Louise Thwaites, Yael Bensoussan, Bradford J. Wood
2023	J	`jnl`	Critical Learning Periods Emerge Even in Deep Linear Networks. CoRR Michael Kleinman, Alessandro Achille, Stefano Soatto
2023	A*	`conf`	Critical Learning Periods for Multisensory Integration in Deep Networks. CVPR Michael Kleinman, Alessandro Achille, Stefano Soatto
2023	A*	`conf`	Gacs-Korner Common Information Variational Autoencoder. NeurIPS Michael Kleinman, Alessandro Achille, Stefano Soatto, Jonathan C. Kao
2023	—	`—`	On the Structure and Learning of Perceptual Representations in Deep Neural Networks Michael Kleinman
2022	J	`jnl`	Critical Learning Periods for Multisensory Integration in Deep Networks. CoRR Michael Kleinman, Alessandro Achille, Stefano Soatto
2022	J	`jnl`	Gacs-Korner Common Information Variational Autoencoder. CoRR Michael Kleinman, Alessandro Achille, Stefano Soatto, Jonathan C. Kao
2021	A*	`conf`	A mechanistic multi-area recurrent network model of decision-making. NeurIPS Michael Kleinman, Chandramouli Chandrasekaran, Jonathan C. Kao
2021	A*	`conf`	Learning rule influences recurrent network representations but not attractor structure in decision-making tasks. NeurIPS Brandon McMahan, Michael Kleinman, Jonathan C. Kao
2021	J	`jnl`	Redundant Information Neural Estimation. Entropy Michael Kleinman, Alessandro Achille, Stefano Soatto, Jonathan C. Kao
2021	A*	`conf`	Usable Information and Evolution of Optimal Representations During Training. ICLR Michael Kleinman, Alessandro Achille, Daksh Idnani, Jonathan C. Kao
2020	J	`jnl`	Usable Information and Evolution of Optimal Representations During Training. CoRR Michael Kleinman, Daksh Idnani, Alessandro Achille, Jonathan C. Kao