A model compilation solution for various hardware

A curated awesome list of lists of interview questions. Feel free to contribute! 🎓

Representation and Reference Lowering of ONNX Models in MLIR Compiler Infrastructure

Efficient research work environment setup for computer science and general workflow for Deep Learning experiments

Google Drive direct download of big files

PPNP & APPNP models from "Predict then Propagate: Graph Neural Networks meet Personalized PageRank" (ICLR 2019)

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

Python package built to ease deep learning on graph, on top of existing DL frameworks.

Code implementation of the paper "Neural Cleanse: Identifying and Mitigating Backdoor Attacks in Neural Networks", at IEEE Security and Privacy 2019.

DeepWalk - Deep Learning for Graphs

links to conference publications in graph-based deep learning

Must-read papers on graph neural networks (GNN)

Source code of Practice of Data Structure and Algorithm (2018 fall)