atomicarchitects / nequixLinks
[NeurIPS'25 AI4Mat] Nequix: Training a foundation model for materials on a budget and [arXiv'26] Phonon fine-tuning (PFT)
☆65Updated this week
Alternatives and similar repositories for nequix
Users that are interested in nequix are comparing it to the libraries listed below
Sorting:
- Equivariant machine learning interatomic potentials in JAX.☆83Updated last week
- MESS: Modern Electronic Structure Simulations☆43Updated 4 months ago
- Official repository for the paper "Uncertainty-biased molecular dynamics for learning uniformly accurate interatomic potentials".☆21Updated last year
- MESS: Modern Electronic Structure Simulations☆20Updated last year
- ☆23Updated 2 years ago
- ☆22Updated 9 months ago
- Compute neighbor lists for atomistic systems☆73Updated this week
- Collection of tutorials to use the MACE machine learning force field.☆52Updated 2 weeks ago
- ⚛ download and manipulate atomistic datasets☆48Updated 2 months ago
- [NeurIPS 2024] Official implementation of the Efficiently Scaled Attention Interatomic Potential☆58Updated 4 months ago
- [npj Comp. Mat.] Higher-order equivariant neural networks for charge density prediction in materials☆71Updated 11 months ago
- Universal interatomic potentials for advanced materials modeling☆128Updated this week
- Force-field-enhanced Neural Networks optimized library☆81Updated last month
- Computing representations for atomistic machine learning☆76Updated last week
- Implementation of the Euclidean fast attention (EFA) algorithm☆59Updated last month
- Training Neural Network potentials through customizable routines in JAX.☆61Updated 6 months ago
- Learning neural network potentials from experimental data via Differentiable Trajectory Reweighting☆36Updated last year
- CUDA implementations of MACE models☆23Updated 5 months ago
- [NeurIPS 2024] source code for "A Recipe for Charge Density Prediction"☆39Updated last year
- Alchemical machine learning interatomic potentials☆33Updated last year
- Train, fine-tune, and manipulate machine learning models for atomistic systems☆54Updated this week
- Robust NN MD simulator☆21Updated 2 years ago
- Build neural networks for machine learning force fields with JAX☆132Updated 8 months ago
- an interface to semi-empirical quantum chemistry methods implemented with pytorch☆72Updated last week
- 🌟 [NeurIPS '25 Spotlight] Fair and transparent benchmark of machine learning interatomic potentials (MLIPs), beyond basic error metrics …☆88Updated 2 weeks ago
- Particle-mesh based calculations of long-range interactions in JAX☆23Updated last week
- Atomistic machine learning models you can use everywhere for everything☆33Updated this week
- [TMLR 2024 J2C Certification] Generalizing Denoising to Non-Equilibrium Structures Improves Equivariant Force Fields☆40Updated last year
- Deprecated - see `pair_nequip_allegro`☆44Updated 9 months ago
- [ICLR'24] Symphony: Symmetry-Equivariant Point-Centered Spherical Harmonics for Molecule Generation☆28Updated 11 months ago