mdsunivie / deeperwinLinks
DeepErwin is a python 3.8+ package that implements and optimizes JAX 2.x wave function models for numerical solutions to the multi-electron Schrödinger equation. DeepErwin supports weight-sharing when optimizing wave functions for multiple nuclear geometries and the usage of pre-trained neural network weights to accelerate optimization.
☆63Updated 7 months ago
Alternatives and similar repositories for deeperwin
Users that are interested in deeperwin are comparing it to the libraries listed below
Sorting:
- Reference implementation of "Ab-Initio Potential Energy Surfaces by Pairing GNNs with Neural Wave Functions" (ICLR, 2022) and "Sampling-f…☆31Updated last year
- Supporting code for "Autoregressive neural-network wavefunctions for ab initio quantum chemistry".☆42Updated 3 years ago
- GradDFT is a JAX-based library enabling the differentiable design and experimentation of exchange-correlation functionals using machine l…☆108Updated last year
- PySCF with auto-differentiation☆87Updated last week
- Differentiable Quantum Chemistry (only Differentiable Density Functional Theory and Hartree Fock at the moment)☆118Updated 3 years ago
- ESI-DCAFM-TACO-VDSP Summer School on "Machine Learning for Materials Hard and Soft"☆39Updated 3 years ago
- MESS: Modern Electronic Structure Simulations☆20Updated last year
- Equivariant machine learning interatomic potentials in JAX.☆79Updated last week
- Higher order equivariant graph neural networks for 3D point clouds☆45Updated 2 years ago
- A JAX-based Differentiable Density Functional Theory Framework for Materials☆39Updated 3 weeks ago
- Arbitrary-order derivatives of popular electronic structure methods, such as Hartree-Fock and coupled cluster theory.☆70Updated last year
- Pretrained model for molecular wavefunctions☆46Updated 3 months ago
- Exchange correlation functionals translated from libxc to jax☆46Updated 7 months ago
- Nomalizing flows for orbita-free DFT☆11Updated last year
- Learning neural network potentials from experimental data via Differentiable Trajectory Reweighting☆36Updated last year
- E3x is a JAX library for constructing efficient E(3)-equivariant deep learning architectures built on top of Flax.☆109Updated 7 months ago
- Calculate observables from neural network-based VMC (NN-VMC).☆17Updated 7 months ago
- OpenEquivariance: a fast, open-source GPU JIT kernel generator for the Clebsch-Gordon Tensor Product.☆98Updated last week
- ☆22Updated 6 months ago
- Materials Learning Algorithms. A framework for machine learning materials properties from first-principles data.☆97Updated 2 months ago
- Build neural networks for machine learning force fields with JAX☆125Updated 5 months ago
- [NeurIPS'25 AI4Mat] Nequix: Training a foundation model for materials on a budget.☆50Updated 2 weeks ago
- A JAX library for Density Functional Theory.☆54Updated 5 months ago
- ☆23Updated 2 years ago
- Code repository for "Finding symmetry breaking order parameters with Euclidean Neural Networks"☆16Updated 4 years ago
- Pytorch Implementation of Real Space Quantum Monte Carlo Simulations of Molecular Systems☆29Updated 6 months ago
- Annotated implementations of equivariant (graph) neural networks in Jax: EGNN, SEGNN, NequIP.☆39Updated 8 months ago
- MESS: Modern Electronic Structure Simulations☆42Updated last month
- Self-describing sparse tensor data format for atomistic machine learning and beyond☆89Updated last week
- An implementation of SchNet in JAX and JAX-MD.☆17Updated 3 years ago