Mir Junaid's Projects
Must-read papers on graph neural networks (GNN)
Practice of Graph Neural Network using DGL and pyTorch geometric
Google Research
Implementation of Planar Graph Convolutional Networks in TensorFlow
Graph4nlp is the library for the easy use of Graph Neural Networks for NLP. Welcome to visit our DLG4NLP website (https://dlg4nlp.github.io/index.html) for various learning resources!
Attention over nodes in Graph Neural Networks using PyTorch (NeurIPS 2019)
A Graph Neural Network (Geometric machine learning) for molecular generation
PyTorch implementation of Ryan Keisler's 2022 "Forecasting Global Weather with Graph Neural Networks" paper (https://arxiv.org/abs/2202.07575)
Platform for designing and evaluating Graph Neural Networks (GNN)
Representation learning on large graphs using stochastic graph convolutions.
[ICLR 2020; IPDPS 2019] Fast and accurate minibatch training for deep GNNs and large graphs (GraphSAINT: Graph Sampling Based Inductive Learning Method).
PyTorch implementation of GraphTSNE, ICLRβ19
GraSP: a Graph Signal Processing toolbox for Matlab
Graph Signal Processing in Matlab
Hands On Natural Language Processing with Python, published by Packt
Code for the paper "How Attentive are Graph Attention Networks?" (ICLR'2022)
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KG Inductive Link Prediction Challenge (ILPC) 2022
A Graph Neural Network Library in Jax
Scalable Graph Neural Networks with Deep Graph Library
End-to-end learning on complex multi-edge graphs with latent-graph convolutional networks.
Jupyter notebooks for teaching/learning Python 3
Become a good Machine Learning Engineer
Linear Algebra
A comprehensive collection of recent papers on graph deep learning
Content for Udacity's Machine Learning curriculum
machine learning and deep learning tutorials, articles and other resources
MaSIF- Molecular surface interaction fingerprints. Geometric deep learning to decipher patterns in molecular surfaces.