Variational Inference | Evidence Lower Bound (ELBO) | Intuition & Visualization
![](https://i.ytimg.com/vi/_iNajZR6jY4/mqdefault.jpg)
25:40
Mean Field Approach for Variational Inference | Intuition & General Derivation
![](https://i.ytimg.com/vi/iwEzwTTalbg/mqdefault.jpg)
27:12
Variational Autoencoder - Model, ELBO, loss function and maths explained easily!
![](https://i.ytimg.com/vi/KHVR587oW8I/mqdefault.jpg)
26:24
The Key Equation Behind Probability
![](https://i.ytimg.com/vi/gV1NWMiiAEI/mqdefault.jpg)
15:34
The challenges in Variational Inference (+ visualization)
![](https://i.ytimg.com/vi/OTO1DygELpY/mqdefault.jpg)
8:14
Introduction to Bayesian statistics, part 2: MCMC and the Metropolis–Hastings algorithm
![](https://i.ytimg.com/vi/HBYQvKlaE0A/mqdefault.jpg)
29:54
Understanding Variational Autoencoders (VAEs) | Deep Learning
![](https://i.ytimg.com/vi/u4BJdBCDR9w/mqdefault.jpg)
48:09
Variational Inference: Simple Example (+ Python Demo)
![](https://i.ytimg.com/vi/HUsznqt2V5I/mqdefault.jpg)
15:29