pnkraemer / diffeqzooLinks
A zoo of implementations of differential equation problems in NumPy and JAX. Oscillators, chemical reactions, n-body problems, epidemiological models, IVPs, BVPs, and more.
☆16Updated last year
Alternatives and similar repositories for diffeqzoo
Users that are interested in diffeqzoo are comparing it to the libraries listed below
Sorting:
- Probabilistic ODE solvers are fun, but are they fast? See also: https://github.com/pnkraemer/probdiffeq for JAX code or https://github.c…☆21Updated last year
- Physics-Enhanced Regression for Initial Value Problems☆20Updated last year
- Probabilistic solvers for differential equations in JAX. Adaptive ODE solvers with calibration, state-space model factorisations, and cus…☆53Updated last week
- ☆36Updated 2 years ago
- Training materials for ModelingToolkit and JuliaSim☆38Updated 3 years ago
- Comparsion of Julia's GPU Kernel based ODE solvers with other open-source GPU ODE solvers☆28Updated last year
- Taylor-mode automatic differentiation for higher-order derivatives☆81Updated 2 weeks ago
- ☆40Updated 4 years ago
- Probabilistic numerical finite differences. Compute finite difference weights and differentiation matrices on scattered data sites and wi…☆11Updated 2 years ago
- Implementation of normalizing flows compatible with Bijectors.jl☆43Updated last week
- Fast uncertainty quantification for scientific machine learning (SciML) and differential equations☆71Updated last month
- Probabilistic Numerical Differential Equation solvers via Bayesian filtering and smoothing☆130Updated 2 weeks ago
- No need to train, he's a smooth operator☆45Updated 3 months ago
- Code for paper https://arxiv.org/abs/2306.07961☆53Updated 2 months ago
- A package for multi-dimensional integration using monte carlo methods☆40Updated last year
- Structure Preserving Machine Learning Models in Julia☆53Updated 2 weeks ago
- Fast approximate high-dimensional hierarchical Bayesian inference☆34Updated last year
- Material for a full course on applied nonlinear dynamics, nonlinear timeseries analysis, and complex systems, in Julia☆65Updated last year
- Implementations of single and multi-ellipsoid nested sampling☆47Updated last week
- Latent Differential Equations models in Julia.☆38Updated 3 years ago
- Efficient, Accurate, and Streamlined Training of Physics-Informed Neural Networks☆59Updated 7 months ago
- Fast symbolic derivatives of runtime-generated expressions☆40Updated 3 months ago
- A Review of Sensitivity Methods for Differential Equations☆33Updated 11 months ago
- Implicit Layer Machine Learning via Deep Equilibrium Networks, O(1) backpropagation with accelerated convergence.☆59Updated 3 months ago
- DifferentialEquations.jl with PyTorch☆11Updated 3 years ago
- Automates steady and unsteady adjoints (general solvers and ODEs respectively). Forward and reverse mode algorithmic differentiation arou…☆29Updated last month
- Methods for computational information geometry☆50Updated this week
- Checkpointing for Automatic Differentiation☆58Updated last week
- Why multiple dispatch lets you write composable code☆40Updated 5 years ago
- ParameterEstimation.jl is a Julia package for estimating parameters and initial conditions of ODE models given measurement data.☆30Updated last month