A collection of resources and papers on Diffusion Models

[IJCAI 2023 survey track]A curated list of resources for chemical pre-trained models

Graphic notes on Gilbert Strang's "Linear Algebra for Everyone"

PyGCL: A PyTorch Library for Graph Contrastive Learning

A curated list for awesome self-supervised learning for graphs.

Fairwalk implementation for IJCAI 2019 paper "Fairwalk: Towards Fair Graph Embedding" https://www.ijcai.org/proceedings/2019/456

Code for ICML2019 Paper "Compositional Invariance Constraints for Graph Embeddings"

Dataset Condensation (ICLR21 and ICML21)

Adversarial attacks and defenses on Graph Neural Networks.

Galaxy Network Embedding: A Hierarchical Community Structure Preserving Approach

Recommender Systems Paperlist that I am interested in

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

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

RayS: A Ray Searching Method for Hard-label Adversarial Attack (KDD2020)

Graph Attention Networks (https://arxiv.org/abs/1710.10903)

Build your neural network easy and fast, 莫烦Python中文教学

The beauty of information retrieval.

Programming exercises for the Stanford Unsupervised Feature Learning and Deep Learning Tutorial