Toggle navigation sidebar

Toggle in-page Table of Contents

deep learning for molecules & materials

Overview

A. Math Review

1. Tensors and Shapes

B. Machine Learning

2. Introduction to Machine Learning
3. Regression & Model Assessment
4. Classification
5. Kernel Learning

C. Deep Learning

6. Deep Learning Overview
7. Standard Layers
8. Graph Neural Networks
9. Input Data & Equivariances
10. Equivariant Neural Networks
11. Explaining Predictions
12. Attention Layers
13. Deep Learning on Sequences
14. Variational Autoencoder
15. Normalizing Flows

D. Applications

16. Predicting DFT Energies with GNNs
17. Generative RNN in Browser

E. Contributed Chapters

18. Hyperparameter Tuning
19. Equivariant Neural Network for Predicting Trajectories
20. Pretraining

F. Appendix

21. Style Guide
22. Changelog

G. In Progress

23. Modern Molecular NNs

By Andrew White

repository
open issue

Search

Searching for multiple words only shows matches that contain all words.

By Andrew D. White
© Copyright 2022.

thewhitelab.org