Paper Reading list for Shilling Attack and Defense on Recommender Systems

The code of ICDM'21 paper "Deep Generation of Heterogeneous Networks"

The official implementation of "Robust Preference-Guided Denoising for Graph based Social Recommendation" (WWW'23)

Code for ICML 2018 paper 'Deep k-Means: Re-Training and Parameter Sharing with Harder Cluster Assignments for Compressing Deep Convolutions'

This repository aims to provide links to work about adversarial robustness and privacy security on the Graph-based recommendation system.

Evals is a framework for evaluating LLMs and LLM systems, and an open-source registry of benchmarks.

Reducing Dimensionality method for Nearest Neighbor Search

Benchmarks of approximate nearest neighbor libraries in Python

Pythonic tool for orchestrating machine-learning/high performance/quantum-computing workflows in heterogeneous compute environments.

A Python Library for Graph Outlier Detection (Anomaly Detection)

Evaluate truth inference methods in crowdsourcing under data poisoning attack

A curated collection of adversarial attack and defense on graph data.

AutoX is an efficient automl tool, which is mainly aimed at data mining tasks with tabular data.

OpenMLDB is an open-source machine learning database that provides a feature platform computing consistent features for training and inference.

读过的一些论文，给自己一个总结和交代吧

Including the data set created by himself, the content of the data set includes the evolution of 972 groups of oracle bones, from oracle bones to regular script. Using twin network to explore the l…

A framework for large scale recommendation algorithms.

A Graph Neural Network Library in Jax

Neural building blocks for speaker diarization: speech activity detection, speaker change detection, overlapped speech detection, speaker embedding

Revisiting, benchmarking, and refining Heterogeneous Graph Neural Networks.

申论生成器(

A pytorch adversarial library for attack and defense methods on images and graphs

The source code of kdd2019 project

A Toolbox for Adversarial Robustness Research

Datasets-for-Heterogeneous-Graph

A curated list of adversarial attacks and defenses papers on graph-structured data.

Adversarial learning papers

推荐系统入门教程，在线阅读地址：https://datawhalechina.github.io/fun-rec/

An "annotated" version of the Transformer Paper in the form of a line-by-line implementation to build an English-to-Chinese translator.