Popular GitHub Repositories for Stochastic Differential Equations

pix2tex: Using a ViT to convert images of equations into LaTeX code.

Fit interpretable models. Explain blackbox machine learning.

Genetic Algorithm, Particle Swarm Optimization, Simulated Annealing, Ant Colony Optimization Algorithm,Immune Algorithm, Artificial Fish Swarm Algorithm, Differential Evolution and TSP(Traveling salesman)

Learning in infinite dimension with neural operators.

NMA Computational Neuroscience course

A unified framework for privacy-preserving data analysis and machine learning

Everything about federated learning, including research papers, books, codes, tutorials, videos and beyond

PyTorch implementation for Score-Based Generative Modeling through Stochastic Differential Equations (ICLR 2021, Oral)

Parallel Computing and Scientific Machine Learning (SciML): Methods and Applications (MIT 18.337J/6.338J)

Gaussian processes in TensorFlow

Master Federated Learning in 2 Hours—Run It on Your PC!

Training PyTorch models with differential privacy

Official code for Score-Based Generative Modeling through Stochastic Differential Equations (ICLR 2021, Oral)

Differentiable SDE solvers with GPU support and efficient sensitivity analysis.

An acausal modeling framework for automatically parallelized scientific machine learning (SciML) in Julia. A computer algebra system for integrated symbolics for physics-informed machine learning and automated transformations of differential equations

A PyTorch library entirely dedicated to neural differential equations, implicit models and related numerical methods

[CCS 2021] "DataLens: Scalable Privacy Preserving Training via Gradient Compression and Aggregation" by Boxin Wang*, Fan Wu*, Yunhui Long*, Luka Rimanic, Ce Zhang, Bo Li

[NeurIPS 2023 Spotlight] LightZero: A Unified Benchmark for Monte Carlo Tree Search in General Sequential Decision Scenarios (awesome MCTS)

translate scientific papers in latex, especially arxiv papers

Keras implementation of "One pixel attack for fooling deep neural networks" using differential evolution on Cifar10 and ImageNet