It is a comprehensive resource hub compiling all graph papers accepted at the International Conference on Learning Representations (ICLR) in 2024.

A Python Library for Graph Outlier Detection (Anomaly Detection)

This repository is made for my book: "Data Mining and Big Data Analytics". It contains all the codes and the dataset used in the book.

Representation learning on large graphs using stochastic graph convolutions.

PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models (CIKM 2021)

ADRepository: Real-world anomaly detection datasets

A collection of important graph embedding, classification and representation learning papers with implementations.

BIAN artefacts in Excel

[ICLR 2020; IPDPS 2019] Fast and accurate minibatch training for deep GNNs and large graphs (GraphSAINT: Graph Sampling Based Inductive Learning Method).

A Python Notebook which employs Discontinuity Regression to measure the effectiveness of a bank's debt recovery strategies.

In this repository, we have modified GraphSAGE representation learning code in many ways to implement our proposed "Node-Centric Graph Learning" algorithm from data. We use the proposed algorithm f…

Collection of Data science projects related to Applied Finance

Hands-on codes in Data Science space on Datacamp

Code & data accompanying the ICLR 2020 paper "Reinforcement Learning Based Graph-to-Sequence Model for Natural Question Generation"

🤖⚡ Daily scikit-learn tips

This is the code for the paper "Learning Deep Kernels for Non-Parametric Two-Sample Tests".

Build Graph Nets in Tensorflow

Software used for generating embeddings from large-scale graph-structured data.

Cheat Sheets

95.16% on CIFAR10 with PyTorch

Deep Learning for humans

FAQs in Slack channel of Udacity's PyTorch Scholarship Challenge.

Tensors and Dynamic neural networks in Python with strong GPU acceleration

My notes on PyTorch Scholarship Challenge 2018/2019