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Poster
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Mon 2:30
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D4FT: A Deep Learning Approach to Kohn-Sham Density Functional Theory
Tianbo Li · Min Lin · Zheyuan Hu · Kunhao Zheng · Giovanni Vignale · Kenji Kawaguchi · A. Castro Neto · Kostya Novoselov · shuicheng YAN
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Oral
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Mon 1:30
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D4FT: A Deep Learning Approach to Kohn-Sham Density Functional Theory
Tianbo Li · Min Lin · Zheyuan Hu · Kunhao Zheng · Giovanni Vignale · Kenji Kawaguchi · A. Castro Neto · Kostya Novoselov · shuicheng YAN
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Workshop
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Thu 6:40
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Machine learning approaches to improve the exchange and correlation functional in Density functional Theory
Marivi Fernandez-Serra
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Poster
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Offline Reinforcement Learning with Differentiable Function Approximation is Provably Efficient
Ming Yin · Mengdi Wang · Yu-Xiang Wang
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Poster
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Tue 2:30
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Learning Rates as a Function of Batch Size: A Random Matrix Theory Approach to Neural Network Training
Diego Granziol · Stefan Zohren · S Roberts
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Oral
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Mon 6:10
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Implicit Bias of Large Depth Networks: a Notion of Rank for Nonlinear Functions
Arthur Jacot
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Poster
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Optimal Activation Functions for the Random Features Regression Model
Jianxin Wang · José Bento
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Poster
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Mon 7:30
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Implicit Bias of Large Depth Networks: a Notion of Rank for Nonlinear Functions
Arthur Jacot
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Oral
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Mon 1:20
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Disentanglement with Biological Constraints: A Theory of Functional Cell Types
James Whittington · Will Dorrell · Surya Ganguli · Timothy Behrens
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Poster
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Mon 2:30
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Disentanglement with Biological Constraints: A Theory of Functional Cell Types
James Whittington · Will Dorrell · Surya Ganguli · Timothy Behrens
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Poster
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Understanding Influence Functions and Datamodels via Harmonic Analysis
Nikunj Saunshi · Arushi Gupta · Mark Braverman · Sanjeev Arora
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Poster
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Near-Optimal Deployment Efficiency in Reward-Free Reinforcement Learning with Linear Function Approximation
Dan Qiao · Yu-Xiang Wang
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