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Sampling Algorithms for Machine Learning with Auxiliary Random Variables and Diffusion Models

Curtis McDonald (UC Berkeley)
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Embracing Chaos: How Instability and Implicit Bias Drive Generalization in Deep Networks

Avrajit Ghosh (UC Berkeley)
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Gradient Descent Dominates Ridge: A Statistical View on Implicit Regularization

Jingfeng Wu (UC Berkeley)
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Break
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Quantum Coding and Quantum Fault-Tolerance

Christopher Pattison (UC Berkeley)
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Quantum Metropolis Sampling and its potential application

Jiaqing Jiang (UC Berkeley)
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Tea Time