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ORCIDMichael Kleinman
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2020 – today
- 2024
[c6]Michael Kleinman, Alessandro Achille, Stefano Soatto:
Critical Learning Periods Emerge Even in Deep Linear Networks. ICLR 2024- [i6]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 Wood:
Voice EHR: Introducing Multimodal Audio Data for Health. CoRR abs/2404.01620 (2024) - [i5]Jakub Smékal, Jimmy T. H. Smith, Michael Kleinman, Dan Biderman, Scott W. Linderman:
Towards a theory of learning dynamics in deep state space models. CoRR abs/2407.07279 (2024) - 2023
- [b1]Michael Kleinman:
On the Structure and Learning of Perceptual Representations in Deep Neural Networks. University of California, Los Angeles, USA, 2023 - [c5]Michael Kleinman, Alessandro Achille, Stefano Soatto:
Critical Learning Periods for Multisensory Integration in Deep Networks. CVPR 2023: 24296-24305 - [c4]Michael Kleinman, Alessandro Achille, Stefano Soatto, Jonathan C. Kao:
Gacs-Korner Common Information Variational Autoencoder. NeurIPS 2023 - [i4]Michael Kleinman, Alessandro Achille, Stefano Soatto:
Critical Learning Periods Emerge Even in Deep Linear Networks. CoRR abs/2308.12221 (2023) - 2022
- [i3]Michael Kleinman, Alessandro Achille, Stefano Soatto, Jonathan C. Kao:
Gacs-Korner Common Information Variational Autoencoder. CoRR abs/2205.12239 (2022) - [i2]Michael Kleinman, Alessandro Achille, Stefano Soatto:
Critical Learning Periods for Multisensory Integration in Deep Networks. CoRR abs/2210.04643 (2022) - 2021
- [j1]Michael Kleinman, Alessandro Achille, Stefano Soatto, Jonathan C. Kao
:
Redundant Information Neural Estimation. Entropy 23(7): 922 (2021) - [c3]Michael Kleinman, Alessandro Achille, Daksh Idnani, Jonathan C. Kao:
Usable Information and Evolution of Optimal Representations During Training. ICLR 2021 - [c2]Brandon McMahan, Michael Kleinman, Jonathan C. Kao:
Learning rule influences recurrent network representations but not attractor structure in decision-making tasks. NeurIPS 2021: 21972-21983 - [c1]Michael Kleinman, Chandramouli Chandrasekaran, Jonathan C. Kao:
A mechanistic multi-area recurrent network model of decision-making. NeurIPS 2021: 23152-23165 - 2020
- [i1]Michael Kleinman, Daksh Idnani, Alessandro Achille, Jonathan C. Kao:
Usable Information and Evolution of Optimal Representations During Training. CoRR abs/2010.02459 (2020)
Coauthor Index
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