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21 search results found

Pysindy ⭐ 1,188

A package for the sparse identification of nonlinear dynamical systems from data

Diffrax ⭐ 1,131

Numerical differential equation solvers in JAX. Autodifferentiable and GPU-capable. https://docs.kidger.site/diffrax/

Torchcde ⭐ 361

Differentiable controlled differential equation solvers for PyTorch with GPU support and memory-efficient adjoint backpropagation.

Neuralcde ⭐ 352

Code for "Neural Controlled Differential Equations for Irregular Time Series" (Neurips 2020 Spotlight)

Sysidentpy ⭐ 270

A Python Package For System Identification Using NARMAX Models

Componentarrays.jl ⭐ 258

Arrays with arbitrarily nested named components.

Easy Neural Ode ⭐ 186

Code for the paper "Learning Differential Equations that are Easy to Solve"

Fasterneuraldiffeq ⭐ 52

Code for "'Hey, that's not an ODE:' Faster ODE Adjoints via Seminorms" (ICML 2021)

Koopman operator identification library in Python, compatible with `scikit-learn`

Datadrivendynsyst ⭐ 40

Scripts and notebooks to accompany the book Data-Driven Methods for Dynamic Systems

core C++ library

Dynamical System Identification using python incorporating numerous powerful deep learning methods. (deepSI = deep System Identification)

Latentdiffeq.jl ⭐ 33

Latent Differential Equations models in Julia.

Bifurcationinference.jl ⭐ 23

learning state-space targets in dynamical systems

Deep Early Warnings Pnas ⭐ 23

Repository to accompany the publication 'Deep learning for early warning signals of tipping points', PNAS (2021)

Package for the data-driven representation of non-linear dynamics over manifolds based on a statistical distribution of local phase portrait features. Includes specific example on dynamical systems, synthetic- and real neural datasets. https://agosztolai.github.io/MARBLE/

Geometric Dynamic Variational Autoencoders (GD-VAEs) for learning embedding maps for nonlinear dynamics into general latent spaces. This includes methods for standard latent spaces or manifold latent spaces with specified geometry and topology. The manifold latent spaces can be based on analytic expressions or general point cloud representations.

AI4Science: Efficient data-driven Online Model Learning (OML) / system identification and control

Datafold ⭐ 14

Extended Dynamic Mode Decomposition to extract analytical and predictive from time series data (with dictionary learning, control and streaming options) . Diffusion Maps to extract geometric description from data.

Memoryefficientstablelds ⭐ 6

Codebase associated with paper "Memory-Efficient Learning of Stable Linear Dynamical Systems for Prediction and Control"

Pressio4py ⭐ 6

Python bindings to pressio

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