fengduqianhe

fengduqianhe's Stars

• bitzhangcy/Deep-Learning-Based-Anomaly-Detection

  2569125

• PonderLY/PC-GNN

  (WWW 2021) Source code of PC-GNN

  Language:Python9911021

• snap-stanford/prodigy

  Language:Python82448

• mala-lab/Awesome-Deep-Graph-Anomaly-Detection

  Official repository for survey paper "Deep Graph Anomaly Detection: A Survey and New Perspectives", including diverse types of resources for graph anomaly detection.

  55007

• PersistenceForever/Neural-Question-Generation-Survey-List

  A comprehensive overview of neural question generation across diverse input formats.

  49201

• yixinliu233/D2PT

  [KDD'23] Learning Strong Graph Neural Networks with Weak Information

  Language:Python43223

• QZ-WANG/ACT

  The official PyTorch implementation of Cross-Domain Graph Anomaly Detection via Anomaly-aware Contrastive Alignment (AAAI2023, to appear).

  Language:Python41225

• mala-lab/GGAD

  Official implementation for NeurIPS'24 paper "Generative Semi-supervised Graph Anomaly Detection"

  Language:Python37031

• yixinliu233/G-OOD-D

  [WSDM'23] GOOD-D: On Unsupervised Graph Out-Of-Distribution Detection

  Language:Python37336

• jmjmalik22/Hate-Speech-Detection

  Official implementation of the paper "Deep Learning for Hate Speech Detection -A Comparative Study"

  352114

• dadaguailhb/TCL

  Language:Python2010

• FanzhenLiu/DAGAD

  Source Code for Paper "DAGAD: Data Augmentation for Graph Anomaly Detection" ICDM 2022

  Language:Python18104

• jhkim611/CLAD

  The official source code for "Class Label-aware Graph Anomaly Detection", accepted at CIKM 2023.

  Language:Python15230

• mala-lab/STEN

  Official implementation of ECML PKDD'24 paper 'Self-Supervised Spatial-Temporal Normality Learning for Time Series Anomaly Detection'.

  Language:Python14112

• mala-lab/UNPrompt

  Code for "Zero-shot Generalist Graph Anomaly Detection with Unified Neighborhood Prompts"

  Language:Python14001

• Niuchx/HimNet

  Code for Graph-level Anomaly Detection via Hierarchical Memory Networks (HimNet)

  Language:Python14123

• betterzhou/AugAN

  Code for paper "Improving Generalizability of Graph Anomaly Detection Models via Data Augmentation" (TKDE 2023)

  Language:Python13200

• mala-lab/FAPrompt

  Official PyTorch implementation of "Fine-grained Abnormality Prompt Learning for Zero-shot Anomaly Detection".

  10000

• FelixDJC/NLGAD

  An official source code for paper "Normality Learning-based Graph Anomaly Detection via Multi-Scale Contrastive Learning", accepted by ACM MM 2023.

  Language:Python8212

• LongJin-lab/suppression-connection

  Code for the paper "Robustness Requires Different Structures Than Residual Connection"

  Language:Python5101

• TheMaXiao/DiTMoS

  An implementation of DiTMoS: Delving into Diverse Tiny-Model Selection on Microcontrollers

  Language:Python5100

• FelixDJC/ARISE

  An official source code for paper "ARISE: Graph Anomaly Detection on Attributed Networks via Substructure Awareness", accepted by IEEE TNNLS.

  Language:Python4201

• mala-lab/FCM

  Official PyTorch implementation of "Foreseeing Abnormality: Time Series Anomaly Prediction via Future Context Modeling".

  Language:Python4111

• withchencheng/ECML_PKDD_23_Real

  ECML/PKDD 2023 Paper: Real: A Representative Error-Driven Approach for Active Learning

  Language:Python4100

• chenlincigit/TGC-MTS

  Temporal Gaussian Copula For Clinical MTS

  Language:Python3100

• LongJin-lab/ZeroSNet

  Official Pytorch implementation of paper "Zero Stability Well Predicts Performance of Convolutional Neural Networks"

  Language:Python3100

• mala-lab/DeLoMe

  Code for Graph Continual Learning with Debiased Lossless Memory Replay (DeLoMe)

  Language:Python3010

• mala-lab/AnomalyCLIP

  Official implementation for paper "Anomalyclip: Object-agnostic prompt learning for zero-shot anomaly detection" (ICLR 2024)

  Language:Python200

• Yali-F/HC-GLAD

  This code is for paper "HC-GLAD: Dual Hyperbolic Contrastive Learning for Unsupervised Graph-Level Anomaly Detection" which is submitted to NeurIPS' 2024 and is currently under review. Please don't quote it or use it for any other purpose.

  Language:Python2201

• Goldenhorns/FANFOLD

  Language:Python1102