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a-simple-nn-classifier

A simple neural network classifier for digital image classification

adversarial_image_defenses

Countering Adversarial Image using Input Transformations.

advssl

A Unified Framework for Data Poisoning Attack to Graph-based Semi-supervised Learning

beglobetrotter.github.io

fastgcn

The sample codes for our ICLR18 paper "FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling""

few-shot-gnn

graph2seq

Graph2Seq is a simple code for building a graph-encoder and sequence-decoder for NLP and other AI/ML/DL tasks.

graphsage

Representation learning on large graphs using stochastic graph convolutions.

malware-detection-based-on-api-sequences

nettack

Implementation of the paper "Adversarial Attacks on Neural Networks for Graph Data".

nlp_adversarial_examples

Implementation code for the paper "Generating Natural Language Adversarial Examples"

omniglot

Omniglot data set for one-shot learning

pa-gnn

Implementation of paper "Transferring Robustness for Graph Neural Network Against Poisoning Attacks".

pig-latin-translator

A Pig Latin translator using sequence-to-sequence model

privacy-preserving-social-network-embedding

Implementation of Adversarial Privacy Graph Embedding in TensorFlow

problem-algorithm

Programming problems and their corresponding Python solutions

pygcn

Graph Convolutional Networks in PyTorch

pytorch-graphsage

Representation learning on large graphs using stochastic graph convolutions.

pytorch-learning

pytorch-optimize

A simple black-box optimization framework to train your pytorch models for optimizing non-differentiable objectives

pytorch_examples

A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.