Pre-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
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Updated
Jun 30, 2026 - Julia
Pre-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
Neural Laplace: Differentiable Laplace Reconstructions for modelling any time observation with O(1) complexity.
Rehuel is a simple C++11 library for solving ordinary differential equations with (implicit) Runge-Kutta methods.
This repo contains the code for the paper "Data-driven discovery of multiscale chemical reactions governed by the law of mass action"
MathSoftDevelopment
Lightweight library for solving initial value problem for ordinary differential equations
Solver for the one dimensional Kuramoto-Sivashinsky using the ETDRK4 method.
Rosenbrock solver for stiff problems, chemical kinetics and chaotic attractors. Zero-heap, bare-metal ready.
A framework to implement CHEMically reacting Method Of Characteristics for supersonic reacting flows.
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