#Differential-equations
Showing 27 of 27 repositories tagged #differential-equations, ranked by stars
Multi-language suite for high-performance solvers of differential equations and scientific machine learning (SciML) components. Ordinary differential equations (ODEs), stochastic differential equations (SDEs), delay differential equations (DDEs), differential-algebraic equations (DAEs), and more in Julia.
Numerical differential equation solvers in JAX. Autodifferentiable and GPU-capable. https://docs.kidger.site/diffrax/
Differentiable SDE solvers with GPU support and efficient sensitivity analysis.
Physics-Informed Neural Networks (PINN) Solvers of (Partial) Differential Equations for Scientific Machine Learning (SciML) accelerated simulation
A library for solving differential equations using neural networks based on PyTorch, used by multiple research groups around the world, including at Harvard IACS.
Physics-Informed Neural networks for Advanced modeling
Tutorials for doing scientific machine learning (SciML) and high-performance differential equation solving with open source software.
Code for "Neural Controlled Differential Equations for Irregular Time Series" (Neurips 2020 Spotlight)
Differentiable controlled differential equation solvers for PyTorch with GPU support and memory-efficient adjoint backpropagation.
Arrays with arbitrarily nested named components.
Reservoir computing utilities for scientific machine learning (SciML)
Rust Scientific Library. ODE, DAE (Runge-Kutta), and PDE solvers. Special functions (Bessel, Elliptic, Beta, Gamma, Erf). Linear algebra. Sparse solvers (MUMPS, UMFPACK). Probability distributions. Tensor calculus. Numerical continuation.
Generative Pre-Trained Physics-Informed Neural Networks Implementation
Open-source, graph-based Python code generator and analysis toolbox for dynamical systems (pre-implemented and custom models). Most pre-implemented models belong to the family of neural population models.
Code for "'Hey, that's not an ODE:' Faster ODE Adjoints via Seminorms" (ICML 2021)
Python library for ODE integration via Taylor's method and LLVM
Neural Laplace: Differentiable Laplace Reconstructions for modelling any time observation with O(1) complexity.
A Julia package for Deep Backwards Stochastic Differential Equation (Deep BSDE) and Feynman-Kac methods to solve high-dimensional PDEs without the curse of dimensionality
This repository contains the source code for "Stochastic data-driven model predictive control using Gaussian processes" (SDD-GP-MPC).
Production-grade ML - F# power & precision guiding Torch performance
Benchmarking, testing, and development tools for differential equations and scientific machine learning (SciML)
Public repository for the proposal “Physics-Informed Machine Learning Simulator for Wildfire Propagation” - MLJC University of Turin - ProjectX2020 Competition (UofT AI)
Reachability analysis for closed-loop control systems in Julia
This project's aim is to provide a sample of my abilities in the form of a challange. The challange is to provide a solution to all exercises in the book Computational Physics by Mark Newman
Covers a variety of computational topics including integration, differential equations, statistical analysis and signal processing.
Tour of the dynamics of change and motion using computational thinking with Python
A set of "real-time" covid19 county-level dashboards w/ national and state choropleths for monitoring localized infection resurgences as distancing, testing and tracing measures evolve.