Woody2357 / 2022-Summer-CourseLinks
This is a repository of the supplementary implementation for the 2022 summer course 'Mathematical Theory and Applications of Deep Learning', taught by Professor Haizhao Yang at Tianyuan Mathematical Center in Central China
☆43Updated 3 years ago
Alternatives and similar repositories for 2022-Summer-Course
Users that are interested in 2022-Summer-Course are comparing it to the libraries listed below
Sorting:
- Tutorials on deep learning, Python, and dissipative particle dynamics☆205Updated 3 years ago
- Group project for Deep Learning: Algorithms and Applications in Peking University 2018 Spring. This is a brief survey, discussion and imp…☆47Updated 7 years ago
- ☆65Updated 3 years ago
- A Deep Learning Library for Modeling Unknown Equations☆25Updated last month
- DeepXDE and PINN☆145Updated 3 years ago
- Implementation of the Deep Ritz method and the Deep Galerkin method☆61Updated 5 years ago
- ☆378Updated 3 years ago
- This repository contains a number of Jupyter Notebooks illustrating different approaches to solve partial differential equations by means…☆181Updated 4 years ago
- Examplary code for NN, MFNN, DynNet, PINNs and CNN☆51Updated 4 years ago
- A comprehensive and fair comparison of two neural operators (with practical extensions) based on FAIR data☆347Updated 2 years ago
- Awesome AI4PDE is a curated list of resources and literature focusing on the intersection of Artificial Intelligence and Partial Differen…☆86Updated 9 months ago
- ☆274Updated 3 years ago
- ETH Zürich Deep Learning in Scientific Computing Master's course 2023☆122Updated last year
- ☆45Updated 7 months ago
- ☆54Updated last year
- PINN, DGM and DRM☆20Updated 2 years ago
- Physics-informed learning of governing equations from scarce data☆167Updated 2 years ago
- We develop a custom ML routine XNODE-WAN to solve parabolic PDEs with high efficiency.☆11Updated 3 years ago
- ☆50Updated 2 years ago
- Basic implementation of physics-informed neural network with pytorch.☆83Updated 3 years ago
- hPINN: Physics-informed neural networks with hard constraints☆153Updated 4 years ago
- Codebase for PINNacle: A Comprehensive Benchmark of Physics-Informed Neural Networks for Solving PDEs.☆386Updated last year
- A large-scale benchmark for machine learning methods in fluid dynamics☆252Updated 2 months ago
- hp-VPINNs: variational physics-informed neural network with domain decomposition is a general framework to solve differential equations☆87Updated 4 months ago
- PINNs-Demo☆13Updated 3 years ago
- Geometry-Aware Fourier Neural Operator (Geo-FNO)☆297Updated 7 months ago
- This repository is the official project page of the course AI in the Sciences and Engineering, ETH Zurich.☆319Updated 7 months ago
- ☆77Updated 2 years ago
- when using, please cite "Bayesian Physics-Informed Neural Networks for real-world nonlinear dynamical systems", CMAME, https://doi.org/1…☆83Updated 3 years ago
- Companion code for "Solving Nonlinear and High-Dimensional Partial Differential Equations via Deep Learning" by A. Al-Aradi, A. Correia, …☆123Updated 6 years ago