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

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

Representation learning on large graphs using stochastic graph convolutions.

Implementation of Adversarial Privacy Graph Embedding in TensorFlow

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

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

Graph Convolutional Networks in PyTorch

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

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

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

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

Omniglot data set for one-shot learning

Countering Adversarial Image using Input Transformations.

Representation learning on large graphs using stochastic graph convolutions.