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Computational Materials Science Notes
Machine learning
Introduction
Denoising Diffusion Probabilistic Models
Dimensionality Reduction
Introduction to Deep learning
Sequence model
Transformer
Variational Autoencoder (VAE)
Variational Inference with Normalizing Flows
Transfer learning
ML for Materials
Deep tensor neural network (DTNN)
GemNet: Universal Directional Graph Neural Networks for Molecules
Junction Tree VAE - Handwritten Derivation
Junction Tree VAE
Material informatics
MolGAN: An implicit generative model for small molecular graphs
MolGPT
Quantum mechanics
Quantum Mechanics - Handwritten Notes
Atomic simulation
Hartree-Fock
Lecture 2
Lecture 3
Introduction to Quantum Mechanics
Lecture 8
Lecture 5
Python
Coding Practices
Pandas Tutorial: Creating, Reading and Writing
Data visualization
Pandas Tutorial: Indexing, Selecting and Assigning
Pandas
Tutorial
Repository
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Variational Inference with Normalizing Flows
Variational Inference with Normalizing Flows
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