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Computational Materials Science Notes
Machine learning
Introduction
1. Learning Algorithms
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
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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