Schedule
The YouTube playlist is linked here. The page containing the notebooks is linked here.
| Lecture # | Date | Topic | Reading |
|---|---|---|---|
| 1 | Aug 3 | Introduction and Logistics [Slides], [YouTube] | |
| 2 | Aug 7 | Bayes Rule for ML [Slides], [YouTube], [Notebook] | |
| 3 | Aug 10 | Distributions, Sampling, Likelihood [Slides][Youtube] [Notebook on Distributions], [Notebook on likelihood], [Notebook on MLE] | |
| 4 | Aug 14 | Maximum Likelihood Estimation (Univariate Normal) [Slides] [Revision on bias/variance of estimators in context of ML prediction], [SGD is unbiased], [Notebook on likelihood], [Notebook on MLE], [Notebook on biased estimators], [Youtube] | |
| 5 | Aug 17 | MLE for linear and logistic regression [Slides], [Notebook], [Youtube] | |
| 6 | Aug 21 | MAP for coin toss, Multivariate Normal [Slides], [Notebook on MAP], [Youtube] | |
| 7 | Aug 24 | Bayesian Linear Regression [Slides], [Notebook MVN], [Youtube] | |
| 8 | Aug 28 | Laplace Appoximation [Slides], [Notebook], Calculus [Slides], [Notebook] [Youtube] | |
| 9 | Aug 31 | Monte Carlo Sampling [Slides], [[Notebooks]], [Youtube] | |
| 10 | Sep 11 | Monte Carlo Sampling and Sampling from common distributions [Slides], [[Notebooks]], [YouTube] | |
| 11 | Sep 14 | Neural Networks uncertainty [Notebook], [YouTube] | |
| 12 | Sep 18 | Rejection and Importance Sampling [Slides] [Notebook] [YouTube] | |
| 13 | Sep 21 | Practical MCMC [Notebook] [Youtube] | |
| 14 | Sep 25 | MCMC theory [Slides 1 on Markov Chain], [Slides on MCMC] [Markov Chain notebook] | |
| 15 | Oct 5 | Calibration [Youtube], [Notebook], [Tutorial on Calibration] | |
| 16 | Oct 9 | MC Dropout and Deep Ensemble [Youtube], [Notebook] | |
| 17 | Oct 16 | Hierarchical Models, [Notebook], [YouTube] | |
| 18 | Oct 19 | Meta learning: Hypernets and Neural Processes, [Notebook], [YouTube] | |
| 19 | Oct 30 | Meta Learning: SIREN, Coordinate Network, Hypernets, Neural Processes [Notebook], [YouTube] | |
| 20 | Nov 2 | Self-supervised learning [Notebook], [YouTube], [Survey article on SSLs] | |
| 21 | Nov 6 | Active Learning [Notebook], [Interactive article], [YouTube], [Survey Article], [Article on Deep Active Learning] | |
| 22 | Nov 9 | Bayesian Optimisation [Notebook 1 on Motivation], [Notebook 2 on implementation from scratch], [YouTube], [Distill.Pub article], [Other reference] | |
| 23 | Nov 13 | KL divergence, Variational Inference, MC sampling, Reparameterisation [Notebook], [YouTube] | |
| 24 | Nov 16 | Variational Inference-II: ELBO, Coin Toss [Notebook][YouTube] | |
| 25 | Nov 20 | Variational Inference-III: Variational Autoencoders [Notebook], [YouTube], [Article on AutoEncoder variants], [Article on VAE (esp. Bayes rule)] | |
| 26 | Nov 23 | Conformal Prediction?/Neural Processes?/Gaussian Processes? |