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The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
Google Research
A comprehensive machine learning repository containing 30+ notebooks on different concepts, algorithms and techniques.
Code samples from the book Web Scraping with Python http://shop.oreilly.com/product/0636920034391.do
A sequence of Jupyter notebooks featuring the "12 Steps to Navier-Stokes" http://lorenabarba.com/
An Open-Source Python3 tool with SMALL models for recognizing layouts, tables, math formulas (LaTeX), and text in images, converting them into Markdown format. A free alternative to Mathpix, empowe…
About Code release for "Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting" (NeurIPS 2021), https://arxiv.org/abs/2106.13008
Welcome to the Physics-based Deep Learning Book (v0.2)
PyTorch Implementation of Physics-informed Neural Networks
Investigating PINNs
Geometry-Aware Fourier Neural Operator (Geo-FNO)
Tutorials on deep learning, Python, and dissipative particle dynamics
PINN (Physics-Informed Neural Networks) on Navier-Stokes Equations
Implement PINN with high level APIs of TF2.0, including a solution of coupled PDEs with PINN
A collection of Jupyter notebooks providing tutorials on reduced order modeling techniques like DeepONet, FNO, DL-ROM, and POD-DL-ROM. Easily runnable on Google Colab.
A learned semi-lagrangian finite volume method