ASK-Berkeley / EScAIPLinks
[NeurIPS 2024] Official implementation of the Efficiently Scaled Attention Interatomic Potential
☆53Updated last week
Alternatives and similar repositories for EScAIP
Users that are interested in EScAIP are comparing it to the libraries listed below
Sorting:
- Higher-order equivariant neural networks for charge density prediction in materials☆62Updated 7 months ago
- Generate and predict molecular electron densities with Euclidean Neural Networks☆48Updated 2 years ago
- [NeurIPS 2024] source code for "A Recipe for Charge Density Prediction"☆36Updated 9 months ago
- train and use graph-based ML models of potential energy surfaces☆106Updated last week
- Reference implementation of "Ewald-based Long-Range Message Passing for Molecular Graphs" (ICML 2023)☆50Updated 2 years ago
- [ICLR 2025] Official Implementation of "Towards Fast, Specialized Machine Learning Force Fields: Distilling Foundation Models via Energy …☆20Updated 5 months ago
- [ICML'24] Adsorbate Placement via Conditional Denoising Diffusion☆20Updated last year
- Reference implementation of "SpookyNet: Learning force fields with electronic degrees of freedom and nonlocal effects"☆78Updated 3 years ago
- MACE-OFF23 models☆45Updated 8 months ago
- Code for “From Molecules to Materials Pre-training Large Generalizable Models for Atomic Property Prediction”.☆60Updated 11 months 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
- SO3krates and Universal Pairwise Force Field for Molecular Simulation☆132Updated this week
- [TMLR 2024] Generalizing Denoising to Non-Equilibrium Structures Improves Equivariant Force Fields☆38Updated 7 months ago
- Generative materials benchmarking metrics, inspired by guacamol and CDVAE.☆40Updated last year
- GemNet model in TensorFlow, as proposed in "GemNet: Universal Directional Graph Neural Networks for Molecules" (NeurIPS 2021)☆27Updated 2 years ago
- [TMLR 2023] Training and simulating MD with ML force fields☆112Updated 11 months ago
- ☆61Updated last month
- Official implementation of DeepDFT model☆84Updated 2 years ago
- A text-guided diffusion model for crystal structure generation☆64Updated 4 months ago
- ☆30Updated last week
- Particle-mesh based calculations of long-range interactions in PyTorch☆62Updated this week
- LAMMPS pair styles for NequIP and Allegro deep learning interatomic potentials☆53Updated 2 weeks ago
- Build neural networks for machine learning force fields with JAX☆125Updated 4 months ago
- A unified platform for fine-tuning atomistic foundation models in chemistry and materials science☆60Updated last week
- Coarse-grained Diffusion for Metal-Organic Framework Design☆52Updated last year
- Algorithms to analyze and predict molecular structures☆21Updated 3 months ago
- Fair and transparent benchmark of machine learning interatomic potentials (MLIPs), beyond basic error metrics https://openreview.net/foru…☆68Updated 2 weeks ago
- [TMLR 2025] Stability-Aware Training of Machine Learning Force Fields with Differentiable Boltzmann Estimators☆14Updated 7 months ago
- Collection of tutorials to use the MACE machine learning force field.☆48Updated last year
- Equivariant machine learning interatomic potentials in JAX.☆75Updated 5 months ago