wzhi / ODElearning_INNLinks
[ICML 2022] Learning Efficient and Robust Ordinary Differential \\ Equations via Invertible Neural Networks
☆10Updated 2 years ago
Alternatives and similar repositories for ODElearning_INN
Users that are interested in ODElearning_INN are comparing it to the libraries listed below
Sorting:
- Nonparametric Differential Equation Modeling☆54Updated last year
- ☆28Updated 2 years ago
- Reference implementation of Finite Element Networks as proposed in "Learning the Dynamics of Physical Systems from Sparse Observations wi…☆69Updated last year
- Supplementary code for the paper "Stationary Kernels and Gaussian Processes on Lie Groups and their Homogeneous Spaces"☆43Updated last year
- Code for "'Hey, that's not an ODE:' Faster ODE Adjoints via Seminorms" (ICML 2021)☆88Updated 2 years ago
- ☆111Updated 4 years ago
- Learning unknown ODE models with Gaussian processes☆26Updated 7 years ago
- code for "Neural Conservation Laws A Divergence-Free Perspective".☆40Updated 2 years ago
- Supplementary code for the NeurIPS 2020 paper "Matern Gaussian processes on Riemannian manifolds".☆29Updated 8 months ago
- ☆35Updated 3 years ago
- Code for efficiently sampling functions from GP(flow) posteriors☆73Updated 4 years ago
- Refining continuous-in-depth neural networks☆42Updated 3 years ago
- ☆20Updated 2 years ago
- Differentiable interface to FEniCS for JAX☆58Updated 4 years ago
- ☆12Updated 3 years ago
- Differentiable interface to FEniCS/Firedrake for JAX using dolfin-adjoint/pyadjoint☆102Updated last year
- Riemannian Convex Potential Maps☆67Updated 2 years ago
- Second-Order Neural ODE Optimizer, NeurIPS 2021 spotlight☆55Updated 3 years ago
- ☆22Updated 11 months ago
- Repo to the paper "Lie Point Symmetry Data Augmentation for Neural PDE Solvers"☆52Updated 2 years ago
- Geometric Dynamic Variational Autoencoders (GD-VAEs) for learning embedding maps for nonlinear dynamics into general latent spaces. This …☆33Updated 2 weeks ago
- By introducing a differentiable contact model, DiffCoSim extends the applicability of Lagrangian/Hamiltonian-inspired neural networks to …☆36Updated 2 years ago
- ☆22Updated 3 years ago
- ☆43Updated 2 years ago
- Methods and experiments for assumed density SDE approximations☆12Updated 3 years ago
- ☆30Updated 3 years ago
- Deep Generalized Schrödinger Bridge, NeurIPS 2022 Oral☆52Updated 2 years ago
- Deterministic particle dynamics for simulating Fokker-Planck probability flows☆26Updated 2 years ago
- Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"☆171Updated 3 years ago
- A JAX-based research framework for writing differentiable numerical simulators with arbitrary discretizations☆131Updated last year