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Computational Materials Science Notes

Machine learning

Introduction
Introduction to Machine learning
Introduction to Deep learning
Loss function
Denoising Diffusion Probabilistic Models
Dimensionality Reduction
Sequence model
Transformer
Variational Autoencoder (VAE)
Variational Inference with Normalizing Flows
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

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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Variational Inference with Normalizing Flows

Variational Inference with Normalizing Flows#

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Transfer learning

By Harrison Li

© Copyright 2026, Harrison Li.

Last updated on Mar 09, 2026.