MaxH1996 / PaiNN-in-PyGLinks
Implementing PaiNN in Pytorch Geometric
☆14Updated 3 years ago
Alternatives and similar repositories for PaiNN-in-PyG
Users that are interested in PaiNN-in-PyG are comparing it to the libraries listed below
Sorting:
- GemNet model in TensorFlow, as proposed in "GemNet: Universal Directional Graph Neural Networks for Molecules" (NeurIPS 2021)☆27Updated 2 years ago
- This repo contains the datasets used for the paper The Design Space of E(3)-Equivariant Atom-Centered Interatomic Potentials.☆19Updated 3 years ago
- This is a simple but efficient implementation of PaiNN-model for constructing machine learning interatomic potentials☆23Updated 3 years ago
- [NeurIPS 2024] source code for "A Recipe for Charge Density Prediction"☆38Updated 11 months ago
- A library for building equivariant neural networks and a zoo of implementations & examples.☆32Updated 3 years ago
- A Newtonian message passing network for deep learning of interatomic potentials and forces☆45Updated 5 months ago
- Input files for Batzner, S., Musaelian, A., Sun, L., Geiger, M., Mailoa, J. P., Kornbluth, M., ... & Kozinsky, B. (2021). E(3)-equivarian…☆14Updated 5 months ago
- Accelerating Metadynamics-Based Free-Energy Calculations with Adaptive Machine Learning Potentials☆16Updated 4 years ago
- Generate and predict molecular electron densities with Euclidean Neural Networks☆48Updated 2 years ago
- ☆34Updated 2 months ago
- Reference implementation of "SpookyNet: Learning force fields with electronic degrees of freedom and nonlocal effects"☆80Updated 3 years ago
- A framework for using topological data analysis to extract structure/symmetry from scientific systems.☆25Updated 3 years ago
- Descriptors-free Collective Variables From Geometric Graph Neural Networks.☆11Updated 11 months ago
- A light-weight PyTorch extension for equivariant deep learning☆17Updated 9 months ago
- ☆12Updated 8 months ago
- DiffSyn: A Generative Diffusion Approach to Materials Synthesis Planning (Nature Computational Science, under proof)☆15Updated 2 weeks ago
- Official repository for the paper "Uncertainty-biased molecular dynamics for learning uniformly accurate interatomic potentials".☆21Updated last year
- An overview of literature that discusses the use of machine learning for atomistic simulations☆45Updated 2 years ago
- Automated reaction discovery and dataset generation with the growing string method☆21Updated 5 years ago
- ☆23Updated last year
- [ICLR 2025] Official Implementation of "Towards Fast, Specialized Machine Learning Force Fields: Distilling Foundation Models via Energy …☆21Updated 7 months ago
- ☆64Updated 3 weeks ago
- MLP training for molecular systems☆54Updated 2 weeks ago
- Code and Data for "Large Language Models for Inorganic Synthesis Prediction"☆32Updated last year
- Flow matching for accelerated simulation of atomic transport☆51Updated last month
- Robust NN MD simulator☆21Updated 2 years ago
- Depiction of Potential Energy Surfaces☆18Updated 2 months ago
- Benchmarking foundation Machine Learning Potentials with Lattice Thermal Conductivity from Anharmonic Phonons☆16Updated last year
- A molecular simulation package integrating MLFFs in MOFs for DAC☆40Updated last month
- Machine learning exercises for the MolSim course (http://www.acmm.nl/molsim/molsim2023/index.html)☆28Updated last year