google-deepmind / dm_hamiltonian_dynamics_suiteLinks
☆34Updated 3 years ago
Alternatives and similar repositories for dm_hamiltonian_dynamics_suite
Users that are interested in dm_hamiltonian_dynamics_suite are comparing it to the libraries listed below
Sorting:
- [ICLR 2022] Path integral sampler☆47Updated last year
- By introducing a differentiable contact model, DiffCoSim extends the applicability of Lagrangian/Hamiltonian-inspired neural networks to …☆36Updated 2 years ago
- ☆20Updated 2 years ago
- Re-implementation of Hamiltonian Generative Networks paper☆33Updated 2 years ago
- Deep Generalized Schrödinger Bridge, NeurIPS 2022 Oral☆48Updated 2 years ago
- Riemannian Convex Potential Maps☆67Updated 2 years ago
- ☆110Updated 4 years ago
- Neural Laplace: Differentiable Laplace Reconstructions for modelling any time observation with O(1) complexity.☆78Updated 2 months ago
- Contact-Aware Symplectic Integrator Network☆14Updated 2 years ago
- A library implementing the kernels for and experiments using extrinsic gauge equivariant vector field Gaussian Processes☆25Updated 3 years ago
- Supplementary code for the NeurIPS 2020 paper "Matern Gaussian processes on Riemannian manifolds".☆29Updated 5 months ago
- Code for "'Hey, that's not an ODE:' Faster ODE Adjoints via Seminorms" (ICML 2021)☆87Updated 2 years ago
- Code for "Continuous-Time Meta-Learning with Forward Mode Differentiation" (ICLR 2022)☆25Updated 3 years ago
- Supplementary code for the paper "Stationary Kernels and Gaussian Processes on Lie Groups and their Homogeneous Spaces"☆43Updated last year
- A collection of graph neural networks implementations in JAX☆33Updated last year
- [ICML 2022] Learning Efficient and Robust Ordinary Differential \\ Equations via Invertible Neural Networks☆10Updated 2 years ago
- Myriad is a real-world testbed that aims to bridge trajectory optimization and deep learning.☆66Updated last year
- Second-Order Neural ODE Optimizer, NeurIPS 2021 spotlight☆52Updated 3 years ago
- Reference implementation of Finite Element Networks as proposed in "Learning the Dynamics of Physical Systems from Sparse Observations wi…☆69Updated last year
- Wraps PyTorch code in a JIT-compatible way for JAX. Supports automatically defining gradients for reverse-mode AutoDiff.☆54Updated 2 months ago
- ☆50Updated 3 years ago
- Model-Based Reinforcement Learning via Latent-Space Collocation.☆33Updated 2 years ago
- Euclidean Wasserstein-2 optimal transportation☆47Updated last year
- Experiments for Meta-Learning Symmetries by Reparameterization☆56Updated 4 years ago
- Tutorial on amortized optimization for learning to optimize over continuous domains☆243Updated 4 months ago
- ICML 2022: Learning Iterative Reasoning through Energy Minimization☆46Updated 2 years ago
- A PyTorch library for all things nonlinear control and reinforcement learning.☆46Updated 3 years ago
- ☆52Updated 2 years ago
- Gradient-based constrained optimization for JAX☆34Updated 2 years ago
- PyTorch Package For Quasimetric Learning☆42Updated 8 months ago