13 Python Kdd Libraries

GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training @ KDD 2020

GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training Original implementation for paper GCC: Graph Contrastive Coding for Graph Neural N

274 Dec 27, 2022

Code for KDD'20 "Generative Pre-Training of Graph Neural Networks"

GPT-GNN: Generative Pre-Training of Graph Neural Networks GPT-GNN is a pre-training framework to initialize GNNs by generative pre-training. It can be

346 Dec 19, 2022

[KDD 2021, Research Track] DiffMG: Differentiable Meta Graph Search for Heterogeneous Graph Neural Networks

DiffMG This repository contains the code for our KDD 2021 Research Track paper: DiffMG: Differentiable Meta Graph Search for Heterogeneous Graph Neura

24 Nov 29, 2022

KDD CUP 2020 Automatic Graph Representation Learning: 1st Place Solution

KDD CUP 2020: AutoGraph Team: aister Members: Jianqiang Huang, Xingyuan Tang, Mingjian Chen, Jin Xu, Bohang Zheng, Yi Qi, Ke Hu, Jun Lei Team Introduc

96 May 30, 2022

A framework for using LSTMs to detect anomalies in multivariate time series data. Includes spacecraft anomaly data and experiments from the Mars Science Laboratory and SMAP missions.

Telemanom (v2.0) v2.0 updates: Vectorized operations via numpy Object-oriented restructure, improved organization Merge branches into single branch fo

844 Dec 28, 2022

Arbitrary Distribution Modeling with Censorship in Real Time 59 2 60 3 Bidding Advertising for KDD'21

Arbitrary_Distribution_Modeling This repo implements the Neighborhood Likelihood Loss (NLL) and Arbitrary Distribution Modeling (ADM, with Interacting

7 Jan 3, 2023

Towards the D-Optimal Online Experiment Design for Recommender Selection (KDD 2021)

Towards the D-Optimal Online Experiment Design for Recommender Selection (KDD 2021) Contact [email protected] or [email protected] for questions

0 Jan 11, 2022

Code for the KDD 2021 paper 'Filtration Curves for Graph Representation'

Filtration Curves for Graph Representation This repository provides the code from the KDD'21 paper Filtration Curves for Graph Representation. Depende

Machine Learning and Computational Biology Lab

16 Oct 16, 2022

A PyTorch implementation of "Graph Classification Using Structural Attention" (KDD 2018).

GAM ⠀⠀ A PyTorch implementation of Graph Classification Using Structural Attention (KDD 2018). Abstract Graph classification is a problem with practic

259 Dec 5, 2022

A PyTorch implementation of "Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks" (KDD 2019).

ClusterGCN ⠀⠀ A PyTorch implementation of "Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks" (KDD 2019). A

697 Dec 27, 2022

Code for KDD'20 "An Efficient Neighborhood-based Interaction Model for Recommendation on Heterogeneous Graph"

Heterogeneous INteract and aggreGatE (GraphHINGE) This is a pytorch implementation of GraphHINGE model. This is the experiment code in the following w

69 Nov 24, 2022

This project provides an unsupervised framework for mining and tagging quality phrases on text corpora with pretrained language models (KDD'21).

UCPhrase: Unsupervised Context-aware Quality Phrase Tagging To appear on KDD'21...[pdf] This project provides an unsupervised framework for mining and

146 Dec 22, 2022

Code for: Gradient-based Hierarchical Clustering using Continuous Representations of Trees in Hyperbolic Space. Nicholas Monath, Manzil Zaheer, Daniel Silva, Andrew McCallum, Amr Ahmed. KDD 2019.

gHHC Code for: Gradient-based Hierarchical Clustering using Continuous Representations of Trees in Hyperbolic Space. Nicholas Monath, Manzil Zaheer, D

35 Nov 16, 2022

Python Kdd Resources

Python kdd Libraries

GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training @ KDD 2020

Code for KDD'20 "Generative Pre-Training of Graph Neural Networks"

[KDD 2021, Research Track] DiffMG: Differentiable Meta Graph Search for Heterogeneous Graph Neural Networks

KDD CUP 2020 Automatic Graph Representation Learning: 1st Place Solution

A framework for using LSTMs to detect anomalies in multivariate time series data. Includes spacecraft anomaly data and experiments from the Mars Science Laboratory and SMAP missions.

Arbitrary Distribution Modeling with Censorship in Real Time 59 2 60 3 Bidding Advertising for KDD'21

Towards the D-Optimal Online Experiment Design for Recommender Selection (KDD 2021)

Code for the KDD 2021 paper 'Filtration Curves for Graph Representation'

A PyTorch implementation of "Graph Classification Using Structural Attention" (KDD 2018).

A PyTorch implementation of "Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks" (KDD 2019).

Code for KDD'20 "An Efficient Neighborhood-based Interaction Model for Recommendation on Heterogeneous Graph"

This project provides an unsupervised framework for mining and tagging quality phrases on text corpora with pretrained language models (KDD'21).

Code for: Gradient-based Hierarchical Clustering using Continuous Representations of Trees in Hyperbolic Space. Nicholas Monath, Manzil Zaheer, Daniel Silva, Andrew McCallum, Amr Ahmed. KDD 2019.

Python Kdd Resources

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Python kdd Libraries

GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training @ KDD 2020

Code for KDD'20 "Generative Pre-Training of Graph Neural Networks"

[KDD 2021, Research Track] DiffMG: Differentiable Meta Graph Search for Heterogeneous Graph Neural Networks

KDD CUP 2020 Automatic Graph Representation Learning: 1st Place Solution

A framework for using LSTMs to detect anomalies in multivariate time series data. Includes spacecraft anomaly data and experiments from the Mars Science Laboratory and SMAP missions.

Arbitrary Distribution Modeling with Censorship in Real Time 59 2 60 3 Bidding Advertising for KDD'21

Towards the D-Optimal Online Experiment Design for Recommender Selection (KDD 2021)

Code for the KDD 2021 paper 'Filtration Curves for Graph Representation'

A PyTorch implementation of "Graph Classification Using Structural Attention" (KDD 2018).

A PyTorch implementation of "Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks" (KDD 2019).

Code for KDD'20 "An Efficient Neighborhood-based Interaction Model for Recommendation on Heterogeneous Graph"

This project provides an unsupervised framework for mining and tagging quality phrases on text corpora with pretrained language models (KDD'21).

Code for: Gradient-based Hierarchical Clustering using Continuous Representations of Trees in Hyperbolic Space. Nicholas Monath, Manzil Zaheer, Daniel Silva, Andrew McCallum, Amr Ahmed. KDD 2019.