fabianjaeger1 / DLSCLinks
This repository contains the machine learning projects completed for the class "Deep Learning in Scientific Computing" taught at ETH jointly by Siddhartha Mishra and Benjamin Moseley in Spring 2024. The description of the tasks can be found in the PDFs.
☆25Updated last year
Alternatives and similar repositories for DLSC
Users that are interested in DLSC are comparing it to the libraries listed below
Sorting:
- [Neurips 2024] A benchmark suite for autoregressive neural emulation of PDEs. (≥46 PDEs in 1D, 2D, 3D; Differentiable Physics; Unrolled T…☆90Updated 2 weeks ago
- Benchmarking Autoregressive Conditional Diffusion Models for Turbulent Flow Simulation☆100Updated 11 months ago
- PINNs-JAX, Physics-informed Neural Networks (PINNs) implemented in JAX.☆55Updated last year
- Example problems in Physics informed neural network in JAX☆82Updated 2 years ago
- An RL-Gym for Challenge Problems in Data-Driven Modeling and Control of Fluid Dynamics.☆87Updated 4 months ago
- TorchFSM: Fourier Spectral Method with PyTorch☆52Updated 2 weeks ago
- AL4PDE: A Benchmark for Active Learning for Neural PDE Solvers☆29Updated 6 months ago
- ☆214Updated last year
- Bootcamp notebooks☆61Updated 3 months ago
- This repository contains code, which was used to generate large-scale results in the HINTS paper.☆34Updated last year
- Code for the paper "Poseidon: Efficient Foundation Models for PDEs"☆159Updated 7 months ago
- An interpretable data-driven framework for building generative reduced order models with embedded uncertainty quantification☆35Updated 8 months ago
- Code for paper Sparse identification of nonlinear dynamics with Shallow Recurrent Decoder Networks.☆34Updated last week
- Codomain attention neural operator for single to multi-physics PDE adaptation.☆70Updated 5 months ago
- when using, please cite "Bayesian Physics-Informed Neural Networks for real-world nonlinear dynamical systems", CMAME, https://doi.org/1…☆79Updated 3 years ago
- This repository is the official project page of the course AI in the Sciences and Engineering, ETH Zurich.