zhengdao-chen / SRNN
Symplectic Recurrent Neural Networks
☆28Updated 2 years ago
Alternatives and similar repositories for SRNN:
Users that are interested in SRNN are comparing it to the libraries listed below
- Refining continuous-in-depth neural networks☆39Updated 3 years ago
- Re-implementation of Hamiltonian Generative Networks paper☆33Updated 2 years ago
- ☆106Updated 3 years ago
- Reference implementation of Finite Element Networks as proposed in "Learning the Dynamics of Physical Systems from Sparse Observations wi…☆70Updated 10 months ago
- ☆45Updated 4 years ago
- code for "Neural Conservation Laws A Divergence-Free Perspective".☆37Updated 2 years ago
- Code for "'Hey, that's not an ODE:' Faster ODE Adjoints via Seminorms" (ICML 2021)☆87Updated 2 years ago
- ☆19Updated 2 years ago
- Computing gradients and Hessians of feed-forward networks with GPU acceleration☆18Updated last year
- ☆19Updated 2 years ago
- Experiments from the paper "On Second Order Behaviour in Augmented Neural ODEs"☆58Updated 6 months ago
- Augmenting Physical Models with Deep Networks for Complex Dynamics Forecasting☆45Updated last year
- ☆34Updated 3 years ago
- Repo to the paper "Lie Point Symmetry Data Augmentation for Neural PDE Solvers"☆49Updated last year
- AL4PDE: A Benchmark for Active Learning for Neural PDE Solvers☆21Updated last month
- ☆27Updated 3 years ago
- Second-Order Neural ODE Optimizer, NeurIPS 2021 spotlight☆52Updated 3 years ago
- Accompanying code for "Weak form generalized Hamiltonian learning"☆9Updated 4 years ago
- Neural Laplace: Differentiable Laplace Reconstructions for modelling any time observation with O(1) complexity.☆75Updated last month
- ☆21Updated 5 months ago
- Code for "Symplectic Adjoint Method for Exact Gradient of Neural ODE with Minimal Memory," NeurIPS, 2021.☆16Updated 3 years ago
- [NeurIPS 2020] Neural Manifold Ordinary Differential Equations (https://arxiv.org/abs/2006.10254)☆117Updated last year
- Hamiltonian Dynamics with Non-Newtonian Momentum for Rapid Sampling☆36Updated 3 years ago
- Nonparametric Differential Equation Modeling☆53Updated last year
- Deterministic particle dynamics for simulating Fokker-Planck probability flows☆24Updated 2 years ago
- repo for paper: Adaptive Checkpoint Adjoint (ACA) method for gradient estimation in neural ODE☆54Updated 4 years ago
- Riemannian Convex Potential Maps☆67Updated 2 years ago
- A collection of graph neural networks implementations in JAX☆32Updated last year
- Package for CGD and ACGD optimizers☆20Updated 2 years ago
- Flow Annealed Importance Sampling Bootstrap (FAB). ICLR 2023.☆56Updated last year