steindoringi / Variational_Integrator_NetworksLinks
☆21Updated 3 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
Sorting:
- Minimal Gaussian process library in JAX with a simple (custom) approach to state management.☆12Updated 2 years ago
- ☆112Updated 4 years ago
- Deep Generalized Schrödinger Bridge, NeurIPS 2022 Oral☆52Updated 3 years ago
- Re-implementation of Hamiltonian Generative Networks paper☆35Updated 3 years ago
- Supplementary code for the paper "Stationary Kernels and Gaussian Processes on Lie Groups and their Homogeneous Spaces"☆45Updated 2 years ago
- Code for efficiently sampling functions from GP(flow) posteriors☆74Updated 5 years ago
- Riemannian Convex Potential Maps☆67Updated 2 years ago
- ☆36Updated 4 years ago
- Symplectic Recurrent Neural Networks☆28Updated 3 years ago
- [ICLR 2022] Path integral sampler☆52Updated 2 years ago
- We simulate a wind tunnel, place a rectangular occlusion in it, and then use gradient descent to turn the occlusion into a wing.☆27Updated 5 years ago
- Nonparametric Differential Equation Modeling☆56Updated last year
- Hamiltonian Dynamics with Non-Newtonian Momentum for Rapid Sampling☆36Updated 4 years ago
- ☆52Updated 2 years ago
- A collection of graph neural networks implementations in JAX☆35Updated 2 years ago
- [ICML 2022] Learning Efficient and Robust Ordinary Differential \\ Equations via Invertible Neural Networks☆10Updated 2 years ago
- PyTorch implementation of Hamiltonian deep neural networks.☆23Updated 4 years ago
- Bayesian algorithm execution (BAX)☆55Updated 4 years ago
- A library implementing the kernels for and experiments using extrinsic gauge equivariant vector field Gaussian Processes☆26Updated 4 years ago
- By introducing a differentiable contact model, DiffCoSim extends the applicability of Lagrangian/Hamiltonian-inspired neural networks to …☆38Updated 3 years ago
- ☆28Updated 3 years ago
- Code for "'Hey, that's not an ODE:' Faster ODE Adjoints via Seminorms" (ICML 2021)☆89Updated 3 years ago
- A repository with implementations of major papers on Gaussian Process regression models, implemented from scratch in Python, notably incl…☆14Updated 3 years ago
- code for "Neural Conservation Laws A Divergence-Free Perspective".☆42Updated 3 years ago
- Second-Order Neural ODE Optimizer, NeurIPS 2021 spotlight☆55Updated 4 years ago
- Modular Gaussian Processes☆16Updated 4 years ago
- Reference implementation of Finite Element Networks as proposed in "Learning the Dynamics of Physical Systems from Sparse Observations wi…☆69Updated last year
- Deterministic particle dynamics for simulating Fokker-Planck probability flows☆26Updated 2 years ago
- Library for normalizing flows and neural flows.☆26Updated 3 years ago
- Supplementary code for the NeurIPS 2020 paper "Matern Gaussian processes on Riemannian manifolds".☆30Updated last year