Variational Inference by Mean Field Approach for the Posterior of the Normal in Python Published 2021-05-17 Download video MP4 360p Recommendations 25:40 Mean Field Approach for Variational Inference | Intuition & General Derivation 25:06 Variational Inference | Evidence Lower Bound (ELBO) | Intuition & Visualization 38:51 Physics-Informed Neural Networks in JAX (with Equinox & Optax) 43:56 Neural Network learns Sine Function with custom backpropagation in Julia 48:09 Variational Inference: Simple Example (+ Python Demo) 15:52 Simple reverse-mode Autodiff in Python 36:09 Machine Learning: Variational Inference 11:33 Evidence Lower Bound (ELBO) - CLEARLY EXPLAINED! 26:50 Neural Networks using Lux.jl and Zygote.jl Autodiff in Julia 1:18:12 Stanford CS330 I Variational Inference and Generative Models l 2022 I Lecture 11 27:59 Neural Networks in pure JAX (with automatic differentiation) 10:46 Plotting the Fourier Transform in Python (DFT/FFT) 18:10 Build Your First Game in Bevy and Rust - Step by Step Tutorial Similar videos 38:21 Deriving the VI by Mean Field Approach for the Posterior of the Normal with unknown mean & precision 35:41 Demystifying Variational Inference (Sayam Kumar) 03:25 Variational Inference (VI) - 1.1 - Intro - Intuition 25:33 [09x12] Bayesian Variational Inference (VI) using RxInfer.jl 56:29 2021 3.1 Variational inference, VAE's and normalizing flows - Rianne van den Berg 46:35 Lecture 14: Approximating Probability Distributions (IV): Variational Methods More results