Popular GitHub Repositories for Puzzle Solvers

Solve puzzles. Improve your pytorch.

Puzzles for learning Triton

Differentiable SDE solvers with GPU support and efficient sensitivity analysis.

Welcome to the Physics-based Deep Learning Book v0.3 - the GenAI Edition

Physics-Informed Neural Networks (PINN) Solvers of (Partial) Differential Equations for Scientific Machine Learning (SciML) accelerated simulation

GUI based Smart Sudoku Solver that tries to extract a sudoku puzzle from a photo and solve it

Pre-built implicit layer architectures with O(1) backprop, GPUs, and stiff+non-stiff DE solvers, demonstrating scientific machine learning (SciML) and physics-informed machine learning methods

High performance ordinary differential equation (ODE) and differential-algebraic equation (DAE) solvers, including neural ordinary differential equations (neural ODEs) and scientific machine learning (SciML)

Chemical reaction network and systems biology interface for scientific machine learning (SciML). High performance, GPU-parallelized, and O(1) solvers in open source software.

Linear solvers in JAX and Equinox. https://docs.kidger.site/lineax

Differentiable controlled differential equation solvers for PyTorch with GPU support and memory-efficient adjoint backpropagation.

Scientific machine learning (SciML) benchmarks, AI for science, and (differential) equation solvers. Covers Julia, Python (PyTorch, Jax), MATLAB, R

Solvers for stochastic differential equations which connect with the scientific machine learning (SciML) ecosystem

Analytics & Machine Learning R Sidekick

Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"

A Library for Advanced Neural PDE Solvers.

Neural network based solvers for partial differential equations and inverse problems :milky_way:. Implementation of physics-informed neural networks in pytorch.

Library for studying Cayley graphs and Schreier coset graphs

This repository is maintained to release dataset and models for multimodal puzzle reasoning.

A library of useful callbacks for hybrid scientific machine learning (SciML) with augmented differential equation solvers