JuliaDynamics/DynamicalSystems.jl

Python Dynamic Mode Decomposition

Highly comparative time-series analysis

catch22: CAnonical Time-series CHaracteristics

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

Multi-language suite for high-performance solvers of differential equations and scientific machine learning (SciML) components. Ordinary differential equations (ODEs), stochastic differential equations (SDEs), delay differential equations (DDEs), differential-algebraic equations (DAEs), and more in Julia.

A Library for Advanced Deep Time Series Models for General Time Series Analysis.

High performance ordinary differential equation (ODE) and differential-algebraic equation (DAE) solvers, including neural ordinary differential equations (neural ODEs) and scientific machine learning (SciML)

Learnable latent embeddings for joint behavioral and neural analysis - Official implementation of CEBRA

A Python package for probabilistic state space modeling with JAX