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Computational Materials Science Notes

Machine learning

Applied math
Introduction to Machine learning
Introduction to Deep learning
Loss function
Activation Function
E(n) Equivariant Graph Neural Networks
Denoising Diffusion Probabilistic Models
Dimensionality Reduction
Sequence model
Transformer
Variational Autoencoder (VAE)
Variational Inference with Normalizing Flows
Reinforcement Learning
Transfer learning

ML for Materials

Junction Tree VAE - Handwritten Derivation
Junction Tree VAE
Material informatics
MolGAN: An implicit generative model for small molecular graphs
MolGPT
SchNet
Deep tensor neural network (DTNN)
GemNet: Universal Directional Graph Neural Networks for Molecules
MACE

Quantum mechanics

Quantum Mechanics - Handwritten Notes

Molecular Dynamics

1. Introduction
Empirical forcefields for modeling organic materials
Forcefields for inorganic materials
Boundary Conditions & Ensembles
Monte Carlo Integration and Monte Carlo Simulation

Computation Chemistry -- papers

Atomic Cluster Expansion (ACE)

Atomic simulation

Force Field 1
Force Field 2
Introduction to Quantum Mechanics
Many-electron system
Hartree-Fock
DFT
DFT2
DFT in solids

Python and torch

Coding Practices
Pandas Tutorial: Creating, Reading and Writing
Data visualization
Pandas Tutorial: Indexing, Selecting and Assigning
Pandas
Tutorial

Agent

Agent architectures
LangGraph
LangGraph

Repository
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.rst

myst_parser.sphinx_ext

Contents

Submodules

`myst_parser.sphinx_ext`#

Sphinx extension for myst_parser.

1. Submodules#

myst_parser.sphinx_ext.directives
myst_parser.sphinx_ext.myst_refs
myst_parser.sphinx_ext.main
myst_parser.sphinx_ext.mathjax

Contents

Submodules

By Harrison Li

© Copyright 2026, Harrison Li.

Last updated on Apr 28, 2026.