hegdepashupati / gaussian-process-odes
Implementation of the work Variational multiple shooting for Bayesian ODEs with Gaussian processes
☆12Updated 2 years ago
Alternatives and similar repositories for gaussian-process-odes:
Users that are interested in gaussian-process-odes are comparing it to the libraries listed below
- Koopman Kernels for Learning Dynamical Systems from Trajectory Data☆24Updated last year
- A Python package to learn the Koopman operator.☆54Updated 4 months ago
- ☆29Updated 2 years ago
- Nonparametric Differential Equation Modeling☆53Updated last year
- ☆15Updated 4 years ago
- Code for efficiently sampling functions from GP(flow) posteriors☆70Updated 4 years ago
- Learning unknown ODE models with Gaussian processes☆26Updated 6 years ago
- A framework for neural network control of dynamical systems over graphs.☆57Updated 2 years ago
- AL4PDE: A Benchmark for Active Learning for Neural PDE Solvers☆21Updated 3 weeks ago
- Data-driven dynamical systems toolbox.☆73Updated last month
- Example code for paper: Automatic Differentiation to Simultaneously Identify Nonlinear Dynamics and Extract Noise Probability Distributio…☆54Updated 2 years ago
- ☆39Updated last year
- ☆27Updated last month
- A repository with implementations of major papers on Gaussian Process regression models, implemented from scratch in Python, notably incl…☆14Updated 2 years ago
- Offline Contextual Bayesian Optimization☆14Updated last year
- A PyTorch library for all things nonlinear control and reinforcement learning.☆45Updated 3 years ago
- Methods and experiments for assumed density SDE approximations☆11Updated 3 years ago
- Official implementation for our paper "Unsupervised Learning of Lagrangian Dynamics from Images for Prediction and Control"☆18Updated 2 years ago
- Neural Networks with Physics-Informed Architectures and Constraints for Dynamical Systems Modeling☆46Updated 3 years ago
- Port-Hamiltonian Approach to Neural Network Training☆22Updated 5 years ago
- This repository contains the source code to perform Geometry-aware Bayesian Optimization (GaBO) on Riemannian manifolds.☆51Updated 3 years ago
- Public code for running Stochastic Gradient Descent on GPs.☆36Updated 5 months ago
- Code for ResDMD: data-driven spectral properties of Koopman Operators☆35Updated last year
- This repository contains the code for the paper "Geometry-aware Bayesian Optimization in Roboticsusing Riemannian Matérn Kernels" (CoRL'2…☆19Updated last year
- [ICML 2022] Learning Efficient and Robust Ordinary Differential \\ Equations via Invertible Neural Networks☆10Updated last year
- Augmenting Physical Models with Deep Networks for Complex Dynamics Forecasting☆45Updated last year
- Koopman operator identification library in Python, compatible with `scikit-learn`☆70Updated 4 months ago
- AutoKoopman - automated Koopman operator methods for data-driven dynamical systems analysis and control.☆72Updated 10 months ago
- Probabilistic solvers for differential equations in JAX. Adaptive ODE solvers with calibration, state-space model factorisations, and cus…☆41Updated 3 weeks ago
- IIB Master's Project: Deep Learning for Koopman Optimal Predictive Control☆45Updated 4 years ago