[DeepBayes2019]: Day 5, Lecture 3. Langevin dynamics for sampling and global optimization
1:27:20
[DeepBayes2019]: Day 5, Lecture 4. Variational inference with implicit and semi-implicit models
25:02
Why do we need MCMC and how does it work? -- Ben Lambert (Oxford)
1:19:47
On Langevin Dynamics in Machine Learning - Michael I. Jordan
49:02
23. Accelerating Gradient Descent (Use Momentum)
12:26
Cédric Villani on Joseph Fourier’s ‘mathematical poem’ • RFI English
32:09
The intuition behind the Hamiltonian Monte Carlo algorithm
1:29:43
Efficient Bayesian inference with Hamiltonian Monte Carlo -- Michael Betancourt (Part 1)
15:40