ORNL / AADLLinks
Anderson Acceleration for Deep Learning
☆13Updated 2 years ago
Alternatives and similar repositories for AADL
Users that are interested in AADL are comparing it to the libraries listed below
Sorting:
- Code for the ICLR 2020 paper "Learning to Control PDEs"☆33Updated 5 years ago
- Python and MATLAB code for Stein Variational sampling methods☆25Updated 6 years ago
- A pyTorch Extension for Applied Mathematics☆39Updated 5 years ago
- Code for "Symplectic Adjoint Method for Exact Gradient of Neural ODE with Minimal Memory," NeurIPS, 2021.☆16Updated 3 years ago
- PyTorch implementation of the OT-Flow approach in arXiv:2006.00104☆52Updated 10 months ago
- Reproduce "Solving high-dimensional partial differential equations using deep learning" by pytorch☆41Updated 6 years ago
- Refining continuous-in-depth neural networks☆39Updated 3 years ago
- Synthetic Lagrangian Turbulence by Generative Diffusion Models☆22Updated 6 months ago
- ☆41Updated 5 years ago
- Code for "'Hey, that's not an ODE:' Faster ODE Adjoints via Seminorms" (ICML 2021)☆87Updated 2 years ago
- ☆33Updated 2 years ago
- Computing gradients and Hessians of feed-forward networks with GPU acceleration☆18Updated last year
- Python notebooks for Optimal Transport between Gaussian Mixture Models☆45Updated 4 years ago
- ☆11Updated 4 years ago
- Bayesian deep convolutional encoder-decoder networks for surrogate modeling and uncertainty quantification☆106Updated 4 years ago
- Symplectic Recurrent Neural Networks☆28Updated 2 years ago
- MeshfreeFlowNet: Physical Constrained Space Time Super-Resolution☆106Updated 4 years ago
- Code and data for paper named: Large language models for automatic equation discovery of nonlinear dynamics☆10Updated 3 months ago
- Second-Order Neural ODE Optimizer, NeurIPS 2021 spotlight☆52Updated 3 years ago
- Source code for "Deep Dynamical Modeling and Control of Unsteady Fluid Flows" from NeurIPS 2018☆48Updated 6 years ago
- Implicit networks can be trained efficiently and simply by using Jacobian-free Backprop (JFB).☆36Updated 3 years ago
- projected Stein variational gradient descent☆10Updated 3 years ago
- ☆28Updated 5 years ago
- Gradient-based Adaptive Markov chain Monte Carlo☆31Updated 5 years ago
- Source code for the ICLR'22 paper on "Half-Inverse Gradients"☆18Updated 3 years ago
- Augmenting Physical Models with Deep Networks for Complex Dynamics Forecasting☆46Updated last year
- The public repository about our joint FINN research project☆36Updated 2 years ago
- Source code for paper "Learning the Solution Operator of Boundary Value Problems using Graph Neural Networks"☆20Updated 10 months ago
- A python/pytorch package for invertible neural networks☆66Updated last year
- Code for the research paper "HINT: Hierarchical Invertible Neural Transport for Density Estimation and Bayesian Inference".☆21Updated 4 years ago