Tutorials¶
NNs in PyTorch¶
Abstract
Some basic tutorials about how one can code Neural networks from scratch. It will feature from scratch as well as how to refactor your code. The ultimate goal is to build Bayesian NN and a Deep GP from scratch. TBD
- Part I - From Scratch
- Part II - Refactored
- eGP2.0 I - Variational GP
Jax n EGPs¶
Abstract
How to use Jax to do derivatives of kernel methods as well as how to use it for GPs with Uncertain Inputs.
- vmap
- jit
- GP From Scratch
- eGP I - Taylor Expansion
- eGP II - MCMC
Old School Manifold Learning¶
Abstract
Some notes about how we can do manifold learning