Notebooks for the Practicals at the Deep Learning Indaba 2022.
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Updated
Apr 3, 2024 - Jupyter Notebook
Notebooks for the Practicals at the Deep Learning Indaba 2022.
This is a repository made for the exam of Advanced Machine Learning for Physics of the course of MSc. in Physics at the Sapienza Universiy of Rome. The purpose of the notebook is recreate the results obtained in the article: "Graph Coloring with Physics-Inspired Graph Neural Networks".
Collection and implementation of a variety of machine learning code examples (notebooks and Python scripts) and projects.
The repository is a collection of Jupyter notebooks showcasing various projects related to graph neural networks (GNNs). Each notebook provides a detailed explanation of the project and its implementation, making it easy for users to understand and replicate the results.
Some of my projects and notebooks related to Machine Learning😀 in one place and not scattered all over GitHub. Check out the README.md in the respective folders first.
In this repository I'm implementing PyTorch based Deep Neural Networks from basic ANN to Advanced Graph Neural Networks. Please suggest if you have any ideas
A small tutorial notebook on Graph Neural Networks, especially Graph Convolutional Networks
Supervised node classification using Graph Convolutional Network (GCN) in DGL.ai.
Python codes and notebooks for the summer school on computer vision and machine learning in CVIT, IIIT Hyderabad, 2019
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