Binary library builder for Sundials for the SciML scientific machine learning open source software organization
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Updated
Nov 21, 2019 - Julia
Binary library builder for Sundials for the SciML scientific machine learning open source software organization
Backend for DiffEqOnline, a webapp for scientific machine learning (SciML)
A wrapper for the Python PyDSTool library for the SciML Scientific Machine Learning organization
Using TensorFlow for physics-informed neural networks for scientific machine learning (SciML)
Solvers for finite element discretizations of PDEs in the SciML scientific machine learning ecosystem
Wrappers for arrays to make broadcasted operations multithreaded and multiprocessed for high-performance scientific machine learning (SciML)
Solvers for Stokes-type equations and saddle-point problems for scientific machine learning (SciML)
Monte Carlo simulation routines for high-performance parallelization of differential equation solvers and scientific machine learning
A helper repository for diffeqpy to enable high-performance differential equation solving scientific machine learning (SciML) in Python
Saving and loading of JuliaDiffEq types for I/O of scientific machine learning (SciML)
A component of the SciML scientific machine learning ecosystem for optimal control
The tools for proper interactions between ApproxFun.jl and DifferentialEquations.jl for pseudospectiral partial differential equation discretizations in scientific machine learning (SciML)
Repository for the Control of Stochastic Quantum Dynamics with Differentiable Programming paper.
Code Listings models of The Years of the Switch and the Dream of The Singularity 2020 CE
Automatic GPU, TPU, FPGA, Xeon Phi, Multithreaded, Distributed, etc. offloading for scientific machine learning (SciML) and differential equations
Automatic detection of sparsity in pure Julia functions for sparsity-enabled scientific machine learning (SciML)
Automatic optimization and parallelization for Scientific Machine Learning (SciML)
Official Implementation of "Opening the Blackbox: Accelerating Neural Differential Equations by Regularizing Internal Solver Heuristics" (ICML 2021)
Latent Differential Equations models in Julia.
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