google-research / neural-structural-optimizationLinks
Neural reparameterization improves structural optimization
☆125Updated 4 years ago
Alternatives and similar repositories for neural-structural-optimization
Users that are interested in neural-structural-optimization are comparing it to the libraries listed below
Sorting:
- Differentiable interface to FEniCS/Firedrake for JAX using dolfin-adjoint/pyadjoint☆103Updated last year
- Differentiable interface to FEniCS for JAX☆58Updated 4 years ago
- PyTorch-FEniCS interface☆102Updated 4 years ago
- A Discussion on Solving Partial Differential Equations using Neural Networks☆66Updated 6 years ago
- ☆112Updated 4 years ago
- ☆73Updated 5 years ago
- A JAX-based research framework for writing differentiable numerical simulators with arbitrary discretizations☆132Updated last year
- Efficient and Scalable Physics-Informed Deep Learning and Scientific Machine Learning on top of Tensorflow for multi-worker distributed c…☆116Updated 3 years ago
- Auto-differentiable and hardware-accelerated force density method☆93Updated 3 weeks ago
- Solver-in-the-Loop: Learning from Differentiable Physics to Interact with Iterative PDE-Solvers☆166Updated 3 years ago
- Package for CGD and ACGD optimizers☆20Updated 3 years ago
- A pyTorch Extension for Applied Mathematics☆40Updated 5 years ago
- Tensorflow implementation of Ordinary Differential Equation Solvers with full GPU support☆223Updated 5 years ago
- Source code for "Deep Dynamical Modeling and Control of Unsteady Fluid Flows" from NeurIPS 2018☆49Updated 6 years ago
- Deep Learning application to the partial differential equations☆30Updated 7 years ago
- ☆194Updated 4 years ago
- Reference implementation of Finite Element Networks as proposed in "Learning the Dynamics of Physical Systems from Sparse Observations wi…☆69Updated last year
- Learning Green's functions of partial differential equations with deep learning.☆72Updated last year
- 18.336 - Fast Methods for Partial Differential and Integral Equations☆184Updated last year
- This repository contains code released by DiffEqML Research☆91Updated 3 years ago
- Computing gradients and Hessians of feed-forward networks with GPU acceleration☆20Updated last year
- Code for "Learning data-driven discretizations for partial differential equations"☆169Updated 2 months ago
- Code for the ICLR 2020 paper "Learning to Control PDEs"☆35Updated 5 years ago
- Deep Hidden Physics Models: Deep Learning of Nonlinear Partial Differential Equations☆280Updated 3 years ago
- Python tools for solving data-constrained finite element problems☆13Updated 3 years ago
- ☆42Updated 5 years ago
- Turning SymPy expressions into PyTorch modules.☆151Updated 2 years ago
- ☆116Updated 6 years ago
- ☆30Updated 3 years ago
- jupyter notebooks for the neural nets and differential equation paper☆28Updated 4 years ago