steindoringi / Variational_Integrator_Networks
☆18Updated 2 years ago
Alternatives and similar repositories for Variational_Integrator_Networks:
Users that are interested in Variational_Integrator_Networks are comparing it to the libraries listed below
- ☆34Updated 3 years ago
- Minimal Gaussian process library in JAX with a simple (custom) approach to state management.☆11Updated last year
- Code for efficiently sampling functions from GP(flow) posteriors☆68Updated 4 years ago
- Re-implementation of Hamiltonian Generative Networks paper☆33Updated 2 years ago
- By introducing a differentiable contact model, DiffCoSim extends the applicability of Lagrangian/Hamiltonian-inspired neural networks to …☆31Updated last year
- Supplementary code for the paper "Stationary Kernels and Gaussian Processes on Lie Groups and their Homogeneous Spaces"☆42Updated last year
- A PyTorch library for all things nonlinear control and reinforcement learning.☆43Updated 3 years ago
- [ICLR 2022] Path integral sampler☆43Updated last year
- Course Website☆9Updated 3 years ago
- Deep Generalized Schrödinger Bridge, NeurIPS 2022 Oral☆47Updated 2 years ago
- A library implementing the kernels for and experiments using extrinsic gauge equivariant vector field Gaussian Processes☆25Updated 3 years ago
- ☆28Updated 2 years ago
- ☆49Updated last year
- ☆38Updated last year
- Modular Gaussian Processes☆15Updated 3 years ago
- Nonparametric Differential Equation Modeling☆53Updated 10 months ago
- Code for "'Hey, that's not an ODE:' Faster ODE Adjoints via Seminorms" (ICML 2021)☆86Updated 2 years ago
- Contact-Aware Symplectic Integrator Network☆11Updated last year
- We simulate a wind tunnel, place a rectangular occlusion in it, and then use gradient descent to turn the occlusion into a wing.☆25Updated 4 years ago
- Symplectic Recurrent Neural Networks☆27Updated 2 years ago
- Meta-learning Gaussian process (GP) priors via PAC-Bayes bounds☆25Updated 11 months ago
- Refining continuous-in-depth neural networks☆39Updated 3 years ago
- A collection of graph neural networks implementations in JAX☆31Updated last year
- Myriad is a real-world testbed that aims to bridge trajectory optimization and deep learning.☆65Updated last year
- A repository with implementations of major papers on Gaussian Process regression models, implemented from scratch in Python, notably incl…☆14Updated 2 years ago
- code for "Neural Conservation Laws A Divergence-Free Perspective".☆35Updated 2 years ago
- ☆80Updated 3 years ago
- Riemannian Convex Potential Maps☆67Updated last year
- Supplementary code for the NeurIPS 2020 paper "Matern Gaussian processes on Riemannian manifolds".☆28Updated 3 years ago
- This repository contains the source code to perform Geometry-aware Bayesian Optimization (GaBO) on Riemannian manifolds.☆50Updated 3 years ago