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A Monte Carlo Tree Search (MCTS) implementation for discovering and optimizing stable intermetallic crystal structures containing uranium and f-block elements by iteratively exploring chemical spac…
Materials Learning Algorithms. A framework for machine learning materials properties from first-principles data.
A modular graph-based Retrieval-Augmented Generation (RAG) system
pyiron - an integrated development environment (IDE) for computational materials science.
A framework for performing active learning for training machine-learned interatomic potentials.
Collection of tools/codes/data used in the article D4DD00265B
Crystal graph convolutional neural networks for predicting material properties.
An inversion-of-control framework for developing modular scientific software.
SciBot is a simple demo of building a domain-specific chatbot for science.
Atomistic Line Graph Neural Network https://scholar.google.com/citations?user=9Q-tNnwAAAAJ https://www.youtube.com/@dr_k_choudhary
Package for performing DQMC simulations of Hubbard and Electron-Phonon Models
Open-source/Oak-Ridge Wang-Landau (OWL): A suite for first-principles based Monte Carlo simulations
LSMS is a code for scalable first principles calculations of materials using multiple scattering theory.
Spin dynamics and generalization to SU(N) coherent states
This is a julia package for advanced Monte Carlo simulations of classical equilibrium and non-equilibrium processes
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
[ARCHIVED] The C++ Standard Library for your entire system. See https://github.com/NVIDIA/cccl
🚴 Call stack profiler for Python. Shows you why your code is slow!
A flexible package manager that supports multiple versions, configurations, platforms, and compilers.
Fast electronic structure solver using gradient-based probing