220 skills found · Page 1 of 8
SciML / SciMLBookParallel Computing and Scientific Machine Learning (SciML): Methods and Applications (MIT 18.337J/6.338J)
DiffEqML / TorchdynA PyTorch library entirely dedicated to neural differential equations, implicit models and related numerical methods
Zymrael / Awesome Neural OdeA collection of resources regarding the interplay between differential equations, deep learning, dynamical systems, control and numerical methods.
raminmh / CfCClosed-form Continuous-time Neural Networks
SciML / DiffEqFlux.jlPre-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
msurtsukov / Neural OdeJupyter notebook with Pytorch implementation of Neural Ordinary Differential Equations
SciML / SciMLTutorials.jlTutorials for doing scientific machine learning (SciML) and high-performance differential equation solving with open source software.
SciML / OrdinaryDiffEq.jlHigh performance ordinary differential equation (ODE) and differential-algebraic equation (DAE) solvers, including neural ordinary differential equations (neural ODEs) and scientific machine learning (SciML)
EmilienDupont / Augmented Neural OdesPytorch implementation of Augmented Neural ODEs :sunflower:
SciML / SciMLSensitivity.jlA component of the DiffEq ecosystem for enabling sensitivity analysis for scientific machine learning (SciML). Optimize-then-discretize, discretize-then-optimize, adjoint methods, and more for ODEs, SDEs, DDEs, DAEs, etc.
SciML / DiffEqBase.jlThe lightweight Base library for shared types and functionality for defining differential equation and scientific machine learning (SciML) problems
SciML / ComponentArrays.jlArrays with arbitrarily nested named components.
SciML / SciMLBenchmarks.jlScientific machine learning (SciML) benchmarks, AI for science, and (differential) equation solvers. Covers Julia, Python (PyTorch, Jax), MATLAB, R
SciML / DiffEqDocs.jlDocumentation for the DiffEq differential equations and scientific machine learning (SciML) ecosystem
SciML / DiffEqGPU.jlGPU-acceleration routines for DifferentialEquations.jl and the broader SciML scientific machine learning ecosystem
analysiscenter / PydensPyDEns is a framework for solving Ordinary and Partial Differential Equations (ODEs & PDEs) using neural networks
mitmath / 18S096SciML18.S096 - Applications of Scientific Machine Learning
jacobjinkelly / Easy Neural OdeCode for the paper "Learning Differential Equations that are Easy to Solve"
SciML / DiffEqOperators.jlLinear operators for discretizations of differential equations and scientific machine learning (SciML)
martenlienen / TorchodeA parallel ODE solver for PyTorch
