QuantumMisaka
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Sample codes for my book on molecular dynamics simulation
An E(3) equivariant Graph Neural Network for predicting electronic Hamiltonian matrix
This add-on to pymatgen provides tools for analyzing diffusion in materials.
CatBench - Benchmark Framework for Machine Learning Interatomic Potentials in Adsorption Energy Predictions
Official implementation of MatterGen -- a generative model for inorganic materials design across the periodic table that can be fine-tuned to steer the generation towards a wide range of property c…
A repository to hold installation recipes and data files for the PET-MAD universal machine-learning interatomic potential
Official implementation of All Atom Diffusion Transformers
A module to obtain and visualize k-vector coefficients and obtain band paths in the Brillouin zone of crystal structures
Object-oriented refactoring of the YARP package
A foundational potential energy dataset for materials
A toolkit for visualizations in materials informatics.
A Windows/macOS/Linux GUI based on Clash
A self-adaptive spin-constraining scheme based on cDFT, operating as an extension to VASP
DeepSPIN method for deep learning potential of magnetic systems
DScribe is a python package for creating machine learning descriptors for atomistic systems.
An analyzing tool for Deep Potential based chemical research.
First-principles statistical mechanical software for the study of multi-component crystalline solids
🍒 Cherry Studio is a desktop client that supports for multiple LLM providers. Support deepseek-r1
CrystalGRW: Generative Modeling of Crystal Structures with Targeted Properties via Geodesic Random Walks
Paper list for equivariant neural network
Perego S. and Bonati L., "Data efficient machine learning potentials for modeling catalytic reactivity via active learning and enhanced sampling", npj Computational Materials 10, 291 (2024)
Code for the paper "Exploration by Random Network Distillation"
SchNet - a deep learning architecture for quantum chemistry