AI4SIM/model-collection
This project contains a collection of deep learning models developed by the AI4Sim team with various partners. This is structured on the basis of use-cases providing canonical PyTorch Lightning pipelines allowing to train neural network models that are able to surrogate various physical processes.
This project offers a collection of pre-built deep learning models designed to simulate complex physical processes more efficiently than traditional methods. It takes raw data from simulations, like those in computational fluid dynamics or weather forecasting, and produces trained neural network models that can quickly predict outcomes. This is ideal for researchers and engineers in scientific computing who need to accelerate simulations without sacrificing accuracy.
Use this if you are a researcher or engineer looking to replace computationally expensive physical simulations with faster, AI-driven surrogate models for tasks like combustion modeling or weather prediction.
Not ideal if you are a beginner looking for a simple, plug-and-play solution without any deep learning or scientific computing background.
Stars
16
Forks
4
Language
Python
License
Apache-2.0
Category
Last pushed
Mar 18, 2026
Commits (30d)
0
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