tum-pbs / pbdl-bookLinks
Welcome to the Physics-based Deep Learning Book v0.3 - the GenAI Edition
☆1,203Updated 3 months ago
Alternatives and similar repositories for pbdl-book
Users that are interested in pbdl-book are comparing it to the libraries listed below
Sorting:
- Links to works on deep learning algorithms for physics problems, TUM-I15 and beyond☆1,843Updated last month
- A differentiable PDE solving framework for machine learning☆1,730Updated last month
- PDEBench: An Extensive Benchmark for Scientific Machine Learning☆993Updated 6 months ago
- All the handwritten notes 📝 and source code files 🖥️ used in my YouTube Videos on Machine Learning & Simulation (https://www.youtube.co…☆1,096Updated 5 months ago
- A library for solving differential equations using neural networks based on PyTorch, used by multiple research groups around the world, i…☆764Updated 3 months ago
- Computational Fluid Dynamics in JAX☆892Updated 2 weeks ago
- ☆1,041Updated 2 weeks ago
- ☆215Updated last year
- OSS library that implements deep learning methods for partial differential equations and much more☆455Updated last month
- Using graph network to solve PDEs☆419Updated 5 months ago
- Physics-Informed Neural networks for Advanced modeling☆590Updated this week
- ☆374Updated last week
- Learning nonlinear operators via DeepONet☆723Updated 3 years ago
- A PyTorch library entirely dedicated to neural differential equations, implicit models and related numerical methods☆1,538Updated last year
- A collection of resources regarding the interplay between differential equations, deep learning, dynamical systems, control and numerical…☆1,493Updated last year
- ETH Zürich Deep Learning in Scientific Computing Master's course 2023☆120Updated last year
- Solve forward and inverse problems related to partial differential equations using finite basis physics-informed neural networks (FBPINNs…☆473Updated this week
- IPython notebooks with demo code intended as a companion to the book "Data-Driven Science and Engineering: Machine Learning, Dynamical Sy…☆948Updated last year
- Lagrangian Neural Networks☆522Updated last month
- Learning in infinite dimension with neural operators.☆3,095Updated last week
- Numerical differential equation solvers in JAX. Autodifferentiable and GPU-capable. https://docs.kidger.site/diffrax/☆1,830Updated last month
- ☆493Updated 7 months ago
- Code for "Discovering Symbolic Models from Deep Learning with Inductive Biases"☆768Updated 2 years ago
- Code accompanying my blog post: So, what is a physics-informed neural network?☆656Updated 3 years ago
- Code for our paper "Hamiltonian Neural Networks"☆491Updated 4 years ago
- Physics Informed Machine Learning Tutorials (Pytorch and Jax)☆609Updated 8 months ago
- IDRLnet, a Python toolbox for modeling and solving problems through Physics-Informed Neural Network (PINN) systematically.☆243Updated last year
- Deep learning for Engineers - Physics Informed Deep Learning☆351Updated last year
- Open-source deep-learning framework for building, training, and fine-tuning deep learning models using state-of-the-art Physics-ML method…☆2,060Updated this week
- This repository is the official project page of the course AI in the Sciences and Engineering, ETH Zurich.☆297Updated 6 months ago