Mathematical Mysteries of Deep Neural Networks - ICTP Colloquium Published 2020-11-25 Download video MP4 360p Download video MP4 720p Recommendations 1:42:18 Intro to Machine Learning & Neural Networks. How Do They Work? 10:39 Liquid Neural Networks, A New Idea That Allows AI To Learn Even After Training 1:28:06 What Every Physicist Should Know About String Theory - ICTP Theoretical Physics Colloquium 2:06:38 This is why Deep Learning is really weird. 3:18:56 2017 Dirac Medal Award Ceremony: Charles H. Bennett, David Deutsch, Peter W. Shor 51:22 Rethinking Physics Informed Neural Networks [NeurIPS'21] 1:12:06 Weak Measurement: A Peephole into the Quantum World - ICTP Colloquium 51:06 Intro to graph neural networks (ML Tech Talks) 13:00 Liquid Neural Networks | Ramin Hasani | TEDxMIT 1:14:40 Lecture 3 | Loss Functions and Optimization 46:00 Dirac Conversation: Edward Witten 1:01:28 How convolutional neural networks work, in depth 1:08:06 Deep Learning Basics: Introduction and Overview 58:12 MIT Introduction to Deep Learning (2023) | 6.S191 1:24:44 Stanford Seminar - Information Theory of Deep Learning, Naftali Tishby 1:10:36 Physics-Informed Neural Networks (PINNs) - An Introduction - Ben Moseley | Jousef Murad 15:27 Greatest Mathematicians and their Discoveries 1:03:08 George Gamow, Gifted Physicist 1:13:09 Lecture 10 | Recurrent Neural Networks 51:40 A Hands-on Introduction to Physics-informed Machine Learning Similar videos 1:04:44 Stéphane MALLAT - Mathematical mysteries of deep neural networks 28:44 Stephane Mallat - Multiscale models for deep neural networks 1:00:34 Stéphane Mallat - Multiscale Models for Image Classification and Physics with Deep Networks 1:05:49 Munich AI Lectures: Stéphane Mallat 26:38 Flatiron Wide Algorithms and Mathematics - Stephane Mallat (October 20, 2020) 58:12 DeepOnet: Learning nonlinear operators based on the universal approximation theorem of operators. 34:26 Mathematical analysis of neural networks - Emily King 20:26 Recent Advances in the Information Theory of Deep Neural Networks and the Computational Benefits... 28:02 Stéphane Mallat: "Open sciences" 45:18 Recent advances in the information theory of deep neural networks 54:07 Jeffrey Pennington | Applied Mathematics (APPM) Department Colloquium 08:18 Naftali Tishby | Information Theory of Deep Learning 04:36 Fundamentals of Machine Learning: The Mystery of Deep Learning 44:19 Stéphane Mallat: Modeling Deep Networks: Network Learning for Image Processing 02:09 Key Mystery about Deep Learning Neural Network 1:16:31 1W-MINDS: Stéphane Mallat, July 2, 2020, Descartes versus Bayes: Harmonic Analysis for High... 1:03:07 Artificial Intelligence: What is it and Why is it so Cool? 1:03:57 Prof. Max Welling: Is the next deep learning disruption in the physical sciences? 20:09 Quick Math Behind Backpropagation - Machine Learning, Deep Learning, Neural Network, Coursera More results