First lecture on Bayesian Deep Learning and Uncertainty Quantification

Eric J. Ma - An Attempt At Demystifying Bayesian Deep Learning

"Bayesian Neural Networks (with VI flavor)" by Yingzhen Li

Визуализация скрытого пространства: PCA, t-SNE, UMAP | Глубокое обучение с анимацией

Bayesian Deep Learning and Probabilistic Model Construction - ICML 2020 Tutorial

Lecture 11 - Introduction to Neural Networks | Stanford CS229: Machine Learning (Autumn 2018)

Самый важный алгоритм в машинном обучении

Miles Cranmer - The Next Great Scientific Theory is Hiding Inside a Neural Network (April 3, 2024)

The Key Equation Behind Probability

Diffusion and Advanced Generative Models third lecture part A

An Introduction to Graph Neural Networks: Models and Applications

Parametrized Stacked Intelligent Metasurfaces forBistatic Integrated Sensing and Communications

History of Bayesian Neural Networks (Keynote talk)

Generative Model That Won 2024 Nobel Prize

LLM и GPT - как работают большие языковые модели? Визуальное введение в трансформеры

Сети Колмогорова-Арнольда (КАН) — что это и как они работают?

Mini Tutorial 6: An Introduction to Uncertainty Quantification for Modeling & Simulation

This is why Deep Learning is really weird.

Uncertainty Quantification and Deep Learning ǀ Elise Jennings, Argonne National Laboratory

4 часа Шопена для обучения, концентрации и релаксации

Using Bayesian Approaches & Sausage Plots to Improve Machine Learning - Computerphile