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:
- ☆29Updated 2 years ago
- Nonparametric Differential Equation Modeling☆53Updated last year
- Supplementary code for the paper "Stationary Kernels and Gaussian Processes on Lie Groups and their Homogeneous Spaces"☆43Updated last year
- Riemannian Convex Potential Maps☆67Updated 2 years ago
- ☆11Updated 3 years ago
- Learning unknown ODE models with Gaussian processes☆26Updated 6 years ago
- Code for "'Hey, that's not an ODE:' Faster ODE Adjoints via Seminorms" (ICML 2021)☆87Updated 2 years ago
- ☆34Updated 3 years ago
- ☆21Updated 8 months ago
- code for "Neural Conservation Laws A Divergence-Free Perspective".☆38Updated 2 years ago
- Supplementary code for the NeurIPS 2020 paper "Matern Gaussian processes on Riemannian manifolds".☆29Updated 4 months ago
- Koopman Kernels for Learning Dynamical Systems from Trajectory Data☆27Updated last year
- Port-Hamiltonian Approach to Neural Network Training☆24Updated 5 years ago
- Refining continuous-in-depth neural networks☆40Updated 3 years ago
- Python and MATLAB code for Stein Variational sampling methods☆25Updated 6 years ago
- Differentiable interface to FEniCS for JAX☆54Updated 4 years ago
- Code for "Symplectic Adjoint Method for Exact Gradient of Neural ODE with Minimal Memory," NeurIPS, 2021.☆16Updated 3 years ago
- Methods and experiments for assumed density SDE approximations☆12Updated 3 years ago
- Neural Fixed-Point Acceleration for Convex Optimization☆29Updated 2 years ago
- Repository for Deterministic Particle Flow Control framework☆10Updated 2 years ago
- ☆20Updated 2 years ago
- Geometric Dynamic Variational Autoencoders (GD-VAEs) for learning embedding maps for nonlinear dynamics into general latent spaces. This …☆30Updated last month
- By introducing a differentiable contact model, DiffCoSim extends the applicability of Lagrangian/Hamiltonian-inspired neural networks to …☆36Updated 2 years ago
- [NeurIPS'19] Deep Equilibrium Models Jax Implementation☆39Updated 4 years ago
- ☆19Updated 3 years ago
- A repository with implementations of major papers on Gaussian Process regression models, implemented from scratch in Python, notably incl…☆14Updated 2 years ago
- Riemannian Optimization Using JAX☆49Updated last year
- Practical tools for quantifying how well a sample approximates a target distribution☆27Updated 4 years ago
- Package for CGD and ACGD optimizers☆20Updated 2 years ago
- A library implementing the kernels for and experiments using extrinsic gauge equivariant vector field Gaussian Processes☆25Updated 3 years ago