sail-sg / d4ftLinks
A JAX library for Density Functional Theory.
☆54Updated 3 weeks ago
Alternatives and similar repositories for d4ft
Users that are interested in d4ft 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…☆57Updated 2 months ago
- Differentiable Quantum Chemistry (only Differentiable Density Functional Theory and Hartree Fock at the moment)☆114Updated 3 years ago
- Supporting code for "Autoregressive neural-network wavefunctions for ab initio quantum chemistry".☆40Updated 3 years ago
- Reference implementation of "Ab-Initio Potential Energy Surfaces by Pairing GNNs with Neural Wave Functions" (ICLR, 2022) and "Sampling-f…☆30Updated last year
- A JAX-based Differentiable Density Functional Theory Framework for Materials☆27Updated this week
- ESI-DCAFM-TACO-VDSP Summer School on "Machine Learning for Materials Hard and Soft"☆39Updated 2 years ago
- Exchange correlation functionals translated from libxc to jax☆45Updated 3 months ago
- Equivariant machine learning interatomic potentials in JAX.☆73Updated 2 months ago
- Corresponding dataset and tools for the AdsorbML manuscript.☆40Updated 5 months ago
- PySCF with auto-differentiation☆81Updated last week
- Code repository for "Finding symmetry breaking order parameters with Euclidean Neural Networks"☆14Updated 4 years ago
- Materials Learning Algorithms. A framework for machine learning materials properties from first-principles data.☆93Updated last month
- MESS: Modern Electronic Structure Simulations☆20Updated 9 months ago
- [TMLR 2024] Generalizing Denoising to Non-Equilibrium Structures Improves Equivariant Force Fields☆37Updated 5 months ago
- Space Group Informed Transformer for Crystalline Materials Generation☆105Updated this week
- E3x is a JAX library for constructing efficient E(3)-equivariant deep learning architectures built on top of Flax.☆108Updated 3 months ago
- Steerable E(3) GNN in jax☆24Updated last year
- GradDFT is a JAX-based library enabling the differentiable design and experimentation of exchange-correlation functionals using machine l…☆101Updated last year
- Learning neural network potentials from experimental data via Differentiable Trajectory Reweighting☆31Updated last year
- a package for developing machine learning-based chemically accurate energy and density functional models☆109Updated 2 months ago
- Higher-order equivariant neural networks for charge density prediction in materials☆59Updated 4 months ago
- OpenEquivariance: a fast, open-source GPU JIT kernel generator for the Clebsch-Gordon Tensor Product.☆76Updated last week
- Build neural networks for machine learning force fields with JAX☆121Updated last month
- MESS: Modern Electronic Structure Simulations☆32Updated last week
- Implementation of a machine learned density functional☆35Updated last year
- ☆22Updated 2 months ago
- ☆23Updated last year
- Code for performing adversarial attacks on atomistic systems using NN potentials☆39Updated 2 years ago
- [TMLR 2025] Stability-Aware Training of Machine Learning Force Fields with Differentiable Boltzmann Estimators☆14Updated 4 months ago
- Robust NN MD simulator☆20Updated last year