
DiffEqFlux
 Referenced in 7 articles
[sw27559]
 differential equations inside of neural networks. We show highlevel functionality for defining neural ordinary...

ANODEs
 Referenced in 8 articles
[sw35084]
 Neural ODEs. We show that Neural Ordinary Differential Equations (ODEs) learn representations that preserve ... that this implies the existence of functions Neural ODEs cannot represent. To address these limitations...

OTFlow
 Referenced in 2 articles
[sw42065]
 mappings obtained by solving a neural ordinary differential equation (ODE). The neural ODE’s dynamics...

Brian
 Referenced in 29 articles
[sw23588]
 Brian” is a new simulator for spiking neural networks, written in Python (http://brian. di.ens.fr ... define models by writing arbitrary differential equations in ordinary mathematical notation. Python scientific libraries...

NeuroDiffEq
 Referenced in 2 articles
[sw32454]
 Python package for solving differential equations with neural networks. NeuroDiffEq is a Python package built ... uses artificial neural networks (ANNs) to solve ordinary and partial differential equations (ODEs and PDEs...

FFJORD
 Referenced in 9 articles
[sw34244]
 complex distribution through an invertible neural network. Likelihoodbased training of these models requires restricting ... transformation is specified by an ordinary differential equation. In this paper, we use Hutchinson ... pass sampling, while allowing unrestricted neural network architectures. We demonstrate our approach on highdimensional...

AntisymmetricRNN
 Referenced in 7 articles
[sw27774]
 System View on Recurrent Neural Networks. Recurrent neural networks have gained widespread use in modeling ... draw connections between recurrent networks and ordinary differential equations. A special form of recurrent networks...

ANNarchy
 Referenced in 2 articles
[sw30220]
 specified using an equationoriented mathematical description similar to the Brian neural simulator. This information ... numerical methods are available to transform ordinary differential equations into an efficient C++code...

Elvet
 Referenced in 1 article
[sw39550]
 Elvet  a neural networkbased differential equation and variational problem solver. We present Elvet ... Python package for solving differential equations and variational problems using machine learning methods. Elvet ... with any system of coupled ordinary or partial differential equations with arbitrary initial and boundary ... these problems is represented as a neural network trained to produce the desired function...

nnde
 Referenced in 1 article
[sw41225]
 networks. Neural networks have been shown to have the ability to solve differential equations [@Yadav ... purePython package for the solution of ordinary and partial differential equations...

StiffPINN
 Referenced in 2 articles
[sw42094]
 laws into the loss functions of the neural network, such that the network not only ... boundary conditions but also satisfies the governing equations. This work first investigates the performance ... chemical kinetic problems with governing equations of stiff ordinary differential equations (ODEs). The results elucidate...

ADOLC
 Referenced in 257 articles
[sw00019]
 ADOLC: Automatic Differentiation of C/C++. We present...

Coq
 Referenced in 1906 articles
[sw00161]
 Coq is a formal proof management system. It...

GAP
 Referenced in 3221 articles
[sw00320]
 GAP is a system for computational discrete algebra...

HSL
 Referenced in 284 articles
[sw00418]
 HSL (formerly the Harwell Subroutine Library) is a...

Isabelle
 Referenced in 719 articles
[sw00454]
 Isabelle is a generic proof assistant. It allows...

LAPACK
 Referenced in 1713 articles
[sw00503]
 LAPACK is written in Fortran 90 and provides...

Macaulay2
 Referenced in 1958 articles
[sw00537]
 Macaulay2 is a software system devoted to supporting...

Magma
 Referenced in 3363 articles
[sw00540]
 Computer algebra system (CAS). Magma is a large...

Maple
 Referenced in 5403 articles
[sw00545]
 The result of over 30 years of cutting...