google-deepmind / inverse_design
☆21Updated last year
Alternatives and similar repositories for inverse_design:
Users that are interested in inverse_design are comparing it to the libraries listed below
- [ICLR23] First deep learning-based surrogate model that jointly learns the evolution model and optimizes computational cost via remeshing☆39Updated last year
- LE-PDE accelerates PDEs' forward simulation and inverse optimization via latent global evolution, achieving significant speedup with SOTA…☆24Updated last year
- ☆14Updated 2 years ago
- Solving Inverse Physics Problems with Score Matching☆23Updated last year
- Code for the ICLR 2020 paper "Learning to Control PDEs"☆32Updated 5 years ago
- ☆50Updated 2 years ago
- Code repository for "Learned Turbulence Modelling with Differentiable Fluid Solvers"☆36Updated 2 years ago
- ☆22Updated 2 years ago
- Generative turbulence model TurbDiff as proposed in "From Zero to Turbulence: Generative Modeling for 3D Flow Simulation", ICLR 2024☆21Updated 2 months ago
- Repo to the paper "Lie Point Symmetry Data Augmentation for Neural PDE Solvers"☆49Updated last year
- Neural SPH☆29Updated 9 months ago
- LagrangeBench: A Lagrangian Fluid Mechanics Benchmarking Suite☆63Updated 3 months ago
- JAX-SPH: A Differentiable Smoothed Particle Hydrodynamics Framework☆61Updated 3 months ago
- code for "Neural Conservation Laws A Divergence-Free Perspective".☆37Updated 2 years ago
- Discovering Conservation Laws using Optimal Transport and Manifold Learning☆17Updated last year
- Official PyTorch implementation of the Vectorized Conditional Neural Field.☆12Updated 8 months ago
- Source code for the ICLR'22 paper on "Half-Inverse Gradients"☆18Updated 3 years ago
- ☆15Updated 4 years ago
- Code for "Aligning Optimization Trajectories with Diffusion Models for Constrained Design Generation" @ NeurIPS 2023☆14Updated last year
- Reference implementation of Finite Element Networks as proposed in "Learning the Dynamics of Physical Systems from Sparse Observations wi…☆69Updated 11 months ago
- Computing gradients and Hessians of feed-forward networks with GPU acceleration☆18Updated last year
- Code repository of the paper "Clifford-Steerable Convolutional Neural Networks"☆47Updated 8 months ago
- ICON for in-context operator learning☆50Updated 2 months ago
- Code for paper "Implicit Neural Spatial Representations for Time-dependent PDEs", ICML 2023☆42Updated last year
- [ICLR 2024] Scaling physics-informed hard constraints with mixture-of-experts.☆32Updated 10 months ago
- Guaranteed Conservation of Momentum for Learning Particle-based Fluid Dynamics (NeurIPS '22)☆51Updated 11 months ago
- MeshGraphNets (MGN)☆62Updated last year
- Scale-invariant Learning by Physics Inversion (NeurIPS 2022)☆10Updated 2 years ago
- Code for Characterizing Scaling and Transfer Learning Behavior of FNO in SciML☆44Updated last year
- Convolutional Differential Operators for Physics-based Deep Learning Study☆24Updated 8 months ago