#Neural-differential-equations
Showing 12 of 12 repositories tagged #neural-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.
A PyTorch library entirely dedicated to neural differential equations, implicit models and related numerical methods
Physics-Informed Neural Networks (PINN) Solvers of (Partial) Differential Equations for Scientific Machine Learning (SciML) accelerated simulation
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.
This repository contains code released by DiffEqML Research
Code for "'Hey, that's not an ODE:' Faster ODE Adjoints via Seminorms" (ICML 2021)
Neural Laplace: Differentiable Laplace Reconstructions for modelling any time observation with O(1) complexity.
Awesome-spatial-temporal-data-mining-packages. Julia and Python resources on spatial and temporal data mining. Mathematical epidemiology as an application. Most about package information. Data Sources Links and Epidemic Repos are also included. Keep updating.