Maurizio Filippone: Functional Priors for Bayesian Deep Learning Published 2023-10-08 Download video MP4 360p Download video MP4 720p Recommendations 1:10:31 Kyunghyun Cho: Generative multitask learning mitigates target-causing confounding 52:46 Miika Aittala: Elucidating the Design Space of Diffusion-Based Generative Models 08:22 Enjoyable "The God Equation" By Michio Kaku (published in 2021) 10:31 Simple Explanation of AutoEncoders 49:03 Jakob Macke: Simulation-based inference and the places it takes us 3:15:38 What is ChatGPT doing...and why does it work? 30:56 Keynote: The big leap of Python 3.13 - Łukasz Langa 14:56 Heroes of Deep Learning: Andrew Ng interviews Ian Goodfellow 3:46:15 Tutorial on Denoising Diffusion-based Generative Modeling: Foundations and Applications 17:38 Intro to Kernel Density Estimation 21:02 The Attention Mechanism in Large Language Models 48:16 Maurizio Filippone (EURECOM): Bayesian Deep Learning 3:57:55 Learn TensorFlow and Deep Learning fundamentals with Python (code-first introduction) Part 2/2 3:57:35 Math for Game Devs [2022, part 1] • Numbers, Vectors & Dot Product 28:09 AI DAY 2023: The Rise of Neural Priors by Prof. Simon Lucey - AIML 44:19 Shane Legg (DeepMind Founder) - 2028 AGI, Superhuman Alignment, New Architectures 11:25 A visual guide to Bayesian thinking 47:53 Arto Klami: Better priors for everyone 48:55 Jensen Huang — NVIDIA's CEO on the Next Generation of AI and MLOps 11:16 P = NP Explained Visually (Big O Notation & Complexity Theory) Similar videos 56:00 AI/ML Seminar Series: Maurizio Filippone and Ba-Hien Tran (5/02/2022) 1:26:05 BA Discussion Webinar: Deep Gaussian Processes for Calibration of Computer Models 1:28:27 A Covariance Function Approach to Prior Specification for Bayesian Neural Networks 2:07:29 Bayesian Neural Networks by Yingzhen Li 1:34:46 [DeepBayes2019]: Day 4, Keynote Lecture 3. Deep Gaussian processes 21:28 Priors for Deep Networks: Limit theorems, pitfalls, open questions 1:34:11 Bayesian Deep Learning and Uncertainty Quantification second tutorial 1:35:43 [DeepBayes2018]: Day 5, Invited talk 3. Deep Gaussian processes 1:02:44 Arka Daw - Uncertainty Quantification with Physics-informed Machine Learning 00:15 A Planar Pendulum_PI-GPR 23:47 Gaussian Processes 52:29 Alexander Ilin: Hierarchical Imitation Learning with Vector Quantized Models More results