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Efficient and Accurate Neural-Network Ansatz for Quantum Monte Carlo
Cartographic rendering and mesh analytics powered by PyVista 🌍
Torch-native C++/CUDA library to accelerate tensor-product layers in MLIPs
High-Performance Symbolic Regression in Python and Julia
Differentiable, Hardware Accelerated, Molecular Dynamics
Deep neural networks for density functional theory Hamiltonian.
Official repository of the Wannier90 code
Qwen3.6 is the large language model series developed by Qwen team, Alibaba Group.
Perplexity open source garden for inference technology
Code for the paper "Online Reasoning Calibration: Test-Time Training Enables Generalizable Conformal LLM Reasoning"
Message Passing Neural Networks for Molecule Property Prediction
OpenMM is a toolkit for molecular simulation using high performance GPU code.
The Open Forcefield Toolkit provides implementations of the SMIRNOFF format, parameterization engine, and other tools. Documentation available at http://open-forcefield-toolkit.readthedocs.io
ScaLAPACK development repository
CheMPS2: a spin-adapted implementation of DMRG for ab initio quantum chemistry
Learning in infinite dimension with neural operators.
The WeightWatcher tool for predicting the accuracy of Deep Neural Networks
A repository for quantum chemistry basis sets
Domain-specific language designed to streamline the development of high-performance GPU/CPU/Accelerators kernels
A c++ program for high-precision atomic structure calculations of one and two valence systems. Uses Hartree-Fock + correlation potential method. Can calculate ionisation cross sections with large o…
ALCHEMI Toolkit-Ops is a collection of optimized batch kernels to accelerate computational chemistry and material science workflows.
🚀 A simple way to launch, train, and use PyTorch models on almost any device and distributed configuration, automatic mixed precision (including fp8), and easy-to-configure FSDP and DeepSpeed support
A sparse attention kernel supporting mix sparse patterns
Undetected version of the Playwright testing and automation library.
A library for accelerating Transformer models on NVIDIA GPUs, including using 8-bit and 4-bit floating point (FP8 and FP4) precision on Hopper, Ada and Blackwell GPUs, to provide better performance…
Numerical differential equation solvers in JAX. Autodifferentiable and GPU-capable. https://docs.kidger.site/diffrax/