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gr_att_analysis

gslb

A comprehensive benchmark of Graph Structure Learning (NeurIPS 2023 Datasets and Benchmarks Track)

handson-ml2

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

hgcn

Hyperbolic Graph Convolutional Networks in PyTorch.

htfl

You only need to configure one file to support model heterogeneity scenarios.

ie-hgcn

Interpretable and Efficient Heterogeneous Graph Convolutional Network, IEEE TKDE 2021

improved-deep-leakage-from-gradients

The code for "Improved Deep Leakage from Gradients" (iDLG).

interpretablecnn

interpretable_cnn

This repository is deprecated, please go to https://github.com/davidsonic/Interpretable_CNNs_via_Feedforward_Design

interpretable_cnns_via_feedforward_design

Official Implementation of Interpretable Convolutional Neural Networks via Feedforward Design Arxiv: https://arxiv.org/abs/1810.02786

interpretable_cnns_via_feedforward_design-1

Official Implementation for FF_designed CNNs

jlgcn

Joing learning of graphs and features

knowledge-graph-papers

Useful research papers to help understand knowledge graph

label_propagation_weak_supervision

Code repository for the paper "Label Propagation with Weak Supervision" (ICLR 23)

lagnn

[ICML 2022] Local Augmentation for Graph Neural Networks

learning-adversarially-robust-representations

Code for the paper: Learning Adversarially Robust Representations via Worst-Case Mutual Information Maximization (https://arxiv.org/abs/2002.11798)

mad-gans

Applied generative adversarial networks (GANs) to do anomaly detection for time series data

marsfl

Federated Learning for Generalization, Robustness, Fairness: A Survey and Benchmark

mdlat

The code for MDLAT

mea-gnn

mia-gnn

Membership Inference Attack against Graph Neural Networks

mia_prune

Membership Inference Attacks and Defenses in Neural Network Pruning

ml-leaks

Code for the paper "ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models"

mlhospital

ml_privacy_meter

Machine Learning Privacy Meter: A tool to quantify the privacy risks of machine learning models with respect to inference attacks, notably membership inference attacks

ml_share_doc

Machine Learning - ppts and code

moon

Model-Contrastive Federated Learning (CVPR 2021)

mopro

MoPro: Webly Supervised Learning

mssgcl

the source code of IJCAI 2023 paper "Multi-Scale subgraph contrastive learning"

mt-mvgcn

source code for TNNLS paper "Multi-Task Representation Learning with Multi-View Graph Convolutional Networks"