benmoseley / DLSC-2023Links
ETH Zürich Deep Learning in Scientific Computing Master's course 2023
☆114Updated 11 months ago
Alternatives and similar repositories for DLSC-2023
Users that are interested in DLSC-2023 are comparing it to the libraries listed below
Sorting:
- ☆200Updated 11 months ago
- This repository is the official project page of the course AI in the Sciences and Engineering, ETH Zurich.☆241Updated 2 months ago
- ☆167Updated last year
- ☆214Updated 3 years ago
- Implementation of the paper "Self-Adaptive Physics-Informed Neural Networks using a Soft Attention Mechanism" [AAAI-MLPS 2021]☆236Updated 3 years ago
- Tutorials on deep learning, Python, and dissipative particle dynamics☆192Updated 3 years ago
- Characterizing possible failure modes in physics-informed neural networks.☆137Updated 3 years ago
- Physics-informed learning of governing equations from scarce data☆145Updated last year
- when using, please cite "Bayesian Physics-Informed Neural Networks for real-world nonlinear dynamical systems", CMAME, https://doi.org/1…☆73Updated 3 years ago
- ☆354Updated 2 years ago
- Solve forward and inverse problems related to partial differential equations using finite basis physics-informed neural networks (FBPINNs…☆432Updated 2 weeks ago
- ☆97Updated 3 years ago
- ☆316Updated 2 months ago
- Extended Physics-Informed Neural Networks (XPINNs): A Generalized Space-Time Domain Decomposition Based Deep Learning Framework for Nonli…☆201Updated 2 years ago
- DeepONet & FNO (with practical extensions)☆312Updated 2 years ago
- ☆145Updated 3 years ago
- ☆182Updated 3 months ago
- ☆128Updated 2 years ago
- Applications of PINOs☆128Updated 2 years ago
- Basic implementation of physics-informed neural network with pytorch.☆71Updated 2 years ago
- ☆138Updated 8 months ago
- This repository contains a number of Jupyter Notebooks illustrating different approaches to solve partial differential equations by means…☆176Updated 4 years ago
- Implementing a physics-informed DeepONet from scratch☆44Updated 2 years ago
- Basic implementation of physics-informed neural networks for solving differential equations☆90Updated 6 months ago
- Introductory workshop on PINNs using the harmonic oscillator☆124Updated 2 months ago
- Using Physics-Informed Deep Learning (PIDL) techniques (W-PINNs-DE & W-PINNs) to solve forward and inverse hydrodynamic shock-tube proble…☆180Updated 2 years ago
- Source code of 'Deep transfer operator learning for partial differential equations under conditional shift'.☆70Updated last year
- PINNs-TF2, Physics-informed Neural Networks (PINNs) implemented in TensorFlow V2.☆129Updated last year
- Generative Pre-Trained Physics-Informed Neural Networks Implementation☆97Updated 4 months ago
- A place to share problems solved with SciANN☆283Updated last year