n-gao / pesnetLinks
Reference implementation of "Ab-Initio Potential Energy Surfaces by Pairing GNNs with Neural Wave Functions" (ICLR, 2022) and "Sampling-free Inference ob Ab-Initio Potential Energy Surface Networks" (ICLR 2023)
☆30Updated last year
Alternatives and similar repositories for pesnet
Users that are interested in pesnet are comparing it to the libraries listed below
Sorting:
- DeepErwin is a python 3.8+ package that implements and optimizes JAX 2.x wave function models for numerical solutions to the multi-electr…☆59Updated 4 months ago
- Supporting code for "Autoregressive neural-network wavefunctions for ab initio quantum chemistry".☆40Updated 3 years ago
- Differentiable Quantum Chemistry (only Differentiable Density Functional Theory and Hartree Fock at the moment)☆114Updated 3 years ago
- Code repository for "Finding symmetry breaking order parameters with Euclidean Neural Networks"☆14Updated 4 years ago
- PySCF with auto-differentiation☆84Updated 2 weeks ago
- Equivariant machine learning interatomic potentials in JAX.☆75Updated 4 months ago
- GradDFT is a JAX-based library enabling the differentiable design and experimentation of exchange-correlation functionals using machine l…☆103Updated last year
- E3x is a JAX library for constructing efficient E(3)-equivariant deep learning architectures built on top of Flax.☆108Updated 4 months ago
- Higher order equivariant graph neural networks for 3D point clouds☆42Updated 2 years ago
- ESI-DCAFM-TACO-VDSP Summer School on "Machine Learning for Materials Hard and Soft"☆39Updated 3 years ago
- A JAX library for Density Functional Theory.☆54Updated 2 months ago
- Learning neural network potentials from experimental data via Differentiable Trajectory Reweighting☆33Updated last year
- Calculate observables from neural network-based VMC (NN-VMC).☆15Updated 4 months ago
- Steerable E(3) GNN in jax☆24Updated last year
- A JAX-based Differentiable Density Functional Theory Framework for Materials☆35Updated last week
- Annotated implementations of equivariant (graph) neural networks in Jax: EGNN, SEGNN, NequIP.☆37Updated 5 months ago
- Exchange correlation functionals translated from libxc to jax☆45Updated 5 months ago
- MESS: Modern Electronic Structure Simulations☆20Updated 11 months ago
- ☆23Updated last year
- Pretrained model for molecular wavefunctions☆39Updated last month
- Arbitrary-order derivatives of popular electronic structure methods, such as Hartree-Fock and coupled cluster theory.☆68Updated last year
- Tools for building equivariant polynomials on reductive Lie groups.☆35Updated 2 years ago
- ☆22Updated 3 months ago
- Nequix: Training a foundation model for materials on a budget.☆31Updated this week
- SE(3) Equivariant Augmented Coupling Flows. NeurIPS 2023.☆24Updated last year
- ☆11Updated last year
- Nomalizing flows for orbita-free DFT☆11Updated 11 months ago
- Reference implementation of "Ewald-based Long-Range Message Passing for Molecular Graphs" (ICML 2023)☆50Updated 2 years ago
- An implementation of SchNet in JAX and JAX-MD.☆17Updated 3 years ago
- repository and website for tutorials on 3d Euclidean equivariant neural networks☆74Updated 4 years ago