1:59:24
Learning with Boolean Threshold Functions, a Statistical Physics Perspective - Raemi Monasson
Institute for Advanced Study
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1:08:17
Phase transitions in high-dimensional statistical inference (Lecture 3) by Remi Monasson
International Centre for Theoretical Sciences
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1:22:59
Phase transitions in high-dimensional statistical inference (Lecture 2) by Remi Monasson
International Centre for Theoretical Sciences
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1:38:55
Giulio Biroli - 1/3 Generative AI and Diffusion Models: a Statistical Physics Analysis
Institut des Hautes Etudes Scientifiques (IHES)
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52:19
Threshold Functions: Approximation, Pseudorandomness and Learning
Microsoft Research
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57:11
Statistical Physics and Machine Learning: A 30 Year Perspective
American Physical Society
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1:00:07
58:59
Gil Kalai: Boolean functions: influence, threshold, and noise
Computational Complexity
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1:01:16
Rémi Monasson - Embedding of Low-Dimensional Attractor Manifolds by Neural Networks
Institut des Hautes Etudes Scientifiques (IHES)
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1:08:58
Low-dimensional attractors and hippocampal representations 2. REMI MONASSON
The Brain Program / IDEAS Research Center
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1:34:19
Phase transitions in high-dimensional statistical inference (Lecture 1)by Remi Monasson
International Centre for Theoretical Sciences
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36:45
Rémi Monasson: "Capacity-resolution trade-off in the optimal learning of multiple low-dimensiona..."
Institute for Pure & Applied Mathematics (IPAM)
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1:03:42
Seminar 9: Surya Ganguli - Statistical Physics of Deep Learning
MIT OpenCourseWare
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