Lists (6)
Stars
Rough Draft of Bike-Bench Repo to Accompany NeurIPS Submission
A list of projects that were or will be featured in Weekly Robotics newsletter
Open-source deep-learning framework for building, training, and fine-tuning deep learning models using state-of-the-art Physics-ML methods
A collection of 100+ specialized Claude Code subagents covering a wide range of development use cases
Design engineering for Claude Code. Craft, memory, and enforcement for consistent UI.
GeoffNN / deeponet-fno
Forked from lu-group/deeponet-fnoDeepONet & FNO (with practical extensions)
A comprehensive and fair comparison of two neural operators (with practical extensions) based on FAIR data
[ICLR 2024] Scaling physics-informed hard constraints with mixture-of-experts.
Links to works on deep learning algorithms for physics problems, TUM-I15 and beyond
PDEBench: An Extensive Benchmark for Scientific Machine Learning
A differentiable PDE solving framework for machine learning
Welcome to the Physics-based Deep Learning Book v0.3 - the GenAI Edition
Lightweight, general, scalable C++ library for finite element methods
🤖 Places where you can learn robotics (and stuff like that) online 🤖
A General Approach to Seismic Inversion Problems using Automatic Differentiation
Automatic Differentiation Library for Computational and Mathematical Engineering
A list of awesome open-source acoustic packages and resources.
An End-to-end Workflow for Adjoint Full Seismic Waveform Inversions
Elastic Full-Waveform Inversion Integrated with PyTorch
Full Waveform Inversion for Transmission Ultrasound Computed Tomography with Transmitting and Receiving Linear Array Transducers based on the Angular Spectrum Method
Official reproducible material for SiameseFWI: A Deep Learning Network for Enhanced Full Waveform Inversion
An Automatic Differentiation-based Waveform Inversion Framework Implemented in PyTorch.
PyTorch implementation of MoDL: Model Based Deep Learning Architecture for Inverse Problems
MoDL: Model-Based Deep Learning Architecture for Inverse Problems
Source code for our recent book entitled Model-Based Deep Learning
For samples codes of the deep unfolding book.