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Neuralpde.jl ⭐ 864

Physics-Informed Neural Networks (PINN) Solvers of (Partial) Differential Equations for Scientific Machine Learning (SciML) accelerated simulation

Diffeqflux.jl ⭐ 810

Universal neural differential equations with O(1) backprop, GPUs, and stiff+non-stiff DE solvers, demonstrating scientific machine learning (SciML) and physics-informed machine learning methods

Neural Ode Metasolver ⭐ 24

Supplementary code for the paper "Meta-Solver for Neural Ordinary Differential Equations" https://arxiv.org/abs/2103.08561

Porthamiltoniannn ⭐ 11

Port-Hamiltonian Approach to Neural Network Training

Pseudo Hamiltonian Neural Networks ⭐ 10

The package phlearn for modelling pseudo-Hamiltonian systems by pseudo-Hamiltonian neural networks (PHNN), for ODEs and PDEs

Control_neuralode ⭐ 9

On the use of NeuralODEs as optimal control policies: I.O. Sandoval, P. Petsagkourakis, E. A. del Rio-Chanona, “Neural ODEs as Feedback Policies for Nonlinear Optimal Control” The 22nd World Congress of the International Federation of Automatic Control (IFAC 2023)

Neural Ode Norm ⭐ 8

Models and code for the ICLR 2020 workshop paper "Towards Understanding Normalization in Neural ODEs"

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