graph-adversarial-learning-literature
by YingtongDou
AI summary
Graph learning research
An exploration of adversarial learning techniques applied to graph data structures
- stars
- 8
- forks
- 3
- watching
- 3
- awesome list
- 1
Similar projects
Found by comparing what the projects do, not just their names.
Graph learner
A deep learning framework for graph representation learning with partially labeled data
Adversarial Visualizer
An online tool allowing users to visualize and generate adversarial examples to deceive neural networks
Spam Detector
An algorithm for detecting spam reviews using reinforcement learning to train robust detectors against strategically synthesized attacks.
Machine learning library
A JavaScript implementation of machine learning algorithms, including logistic regression and decision tree models.
Fraud Detector
An implementation of a graph neural network-based fraud detector designed to counter camouflaged fraudsters
Membership inference studies
A curated collection of papers on membership inference attacks and defenses in machine learning models.
Graph database library
A SPARQL-compliant graph database implemented as a Rust library and exposed to multiple programming languages.
Graph learning framework
A framework for decentralized multi-task learning of graph neural networks on molecular data with guaranteed convergence
Deep Learning Study
A collection of papers and repos on deep learning with noisy labels.
Drug Discovery Survey
Compiles works on applying artificial intelligence in drug discovery to various areas
Chinese Language Model
Trains and evaluates a Chinese language model using adversarial training on a large corpus.
Network reprogramming
This project enables reprogramming of pre-trained neural networks to work on new tasks by fine-tuning them on smaller datasets.
Graph classifier
This project implements a federated learning algorithm for non-IID graph classification tasks by leveraging structural knowledge sharing.
Graph learning framework
A software framework that integrates statistical relational learning and graph neural networks for semi-supervised object classification and unsupervised node representation learning.
Graph learning algorithm
An implementation of an algorithm for learning trajectory representations in temporal graphs
Featured in 1 awesome list
Each link jumps to the spot where the list mentions graph-adversarial-learning-literature.