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Repository of best practices for deep learning in Julia, inspired by fastai
Tools for using AD to optimize tensor networks, built on top of ITensor and AutoHOOT.
Differentiable SDE solvers with GPU support and efficient sensitivity analysis.
|toqito> (Theory of Quantum Information Toolkit) in Python 🐍
A Python SDK for interacting with quantum devices on Amazon Braket
the QASM compilation target, includes QASM frontend and backend
Ground States of Quantum Many Body Lattice Models via Reinforcement Learning
projected entangled pair of states (PEPS), the quantum version
Classical Monte Carlo simulations for lattice spin systems
Hyper optimized contraction trees for large tensor networks and einsums
Symbolic programming for the next generation of numerical software
Nimble: Physics Engine for Biomechanics and Deep Learning
Run ruff, isort, pyupgrade, mypy, pylint, flake8, and more on Jupyter Notebooks
🛠 Python project template generator with batteries included
Tutorials for the paper: "Neural network in quantum many-body physics: a hands-on tutorial"
Track emissions from Compute and recommend ways to reduce their impact on the environment.
Free open public domain football data for the World Cup (incl. Qatar 2022, Russia 2018, Brazil 2014, etc.) and World Cup Quali(fiers)
Clifford circuits, graph states, and other quantum Stabilizer formalism tools.
High-performance automatic differentiation of LLVM and MLIR.
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
Deep learning models for guitar amp/pedal emulation using LSTM with Keras.
Kedro is a toolbox for production-ready data science. It uses software engineering best practices to help you create data engineering and data science pipelines that are reproducible, maintainable,…
A method which combines quantum many-body calculation and unbiased optimizers to automatically learn effective Hamiltonians for quantum magnets