283 Open source projects that are alternatives of or similar to awesome-graph-self-supervised-learning-based-recommendation

An index of recommendation algorithms that are based on Graph Neural Networks.

PyTorch implementation of the InfoNCE loss for self-supervised learning.

PyTorch implementation of SimCLR: supports multi-GPU training and closely reproduces results

📄 Spatial Contrastive Learning for Few-Shot Classification (ECML/PKDD 2021).

Implementation of paper "Self-supervised Learning on Graphs:Deep Insights and New Directions"

Revisiting Contrastive Methods for Unsupervised Learning of Visual Representations. [NeurIPS 2021]

Generalized Deep Metric Learning.

Parametric Instance Classification for Unsupervised Visual Feature Learning, NeurIPS 2020

AdCo: Adversarial Contrast for Efficient Learning of Unsupervised Representations from Self-Trained Negative Adversaries

SimCLRv2 - Big Self-Supervised Models are Strong Semi-Supervised Learners

The PyTorch implementation of Directed Graph Contrastive Learning (DiGCL), NeurIPS-2021

A PyTorch implementation of "SelfGNN: Self-supervised Graph Neural Networks without explicit negative sampling" paper, which appeared in The International Workshop on Self-Supervised Learning for the Web (SSL'21) @ the Web Conference 2021 (WWW'21).

[WACV'22] Code repository for the paper "Self-supervised Video Representation Learning with Cross-Stream Prototypical Contrasting", https://arxiv.org/abs/2106.10137.

This repository contains the code implementation used in the paper Temporally Coherent Embeddings for Self-Supervised Video Representation Learning (TCE).

Code for the paper "DisCont: Self-Supervised Visual Attribute Disentanglement using Context Vectors".

This is the code base for paper "G-SimCLR : Self-Supervised Contrastive Learning with Guided Projection via Pseudo Labelling" by Souradip Chakraborty, Aritra Roy Gosthipaty and Sayak Paul.

Revisiting Graph based Collaborative Filtering: A Linear Residual Graph Convolutional Network Approach, AAAI2020

Awesome Graph Self-Supervised Learning

Making self-supervised learning work on molecules by using their 3D geometry to pre-train GNNs. Implemented in DGL and Pytorch Geometric.

List of Publications in Graph Contrastive Learning

[NeurIPS 2021 Spotlight] Aligning Pretraining for Detection via Object-Level Contrastive Learning

The easiest way to use deep metric learning in your application. Modular, flexible, and extensible. Written in PyTorch.

[WWW 2021] Source code for "Graph Contrastive Learning with Adaptive Augmentation"

official implemntation for "Contrastive Learning with Stronger Augmentations"

Object-aware Contrastive Learning for Debiased Scene Representation (NeurIPS 2021)

S2-BNN: Bridging the Gap Between Self-Supervised Real and 1-bit Neural Networks via Guided Distribution Calibration (CVPR 2021)

Learning Intents behind Interactions with Knowledge Graph for Recommendation, WWW2021

Code and resources on scalable and efficient Graph Neural Networks

Official PyTorch implementation of Contrastive Learning of Musical Representations

Data Science algorithms and topics that you must know. (Newly Designed) Recommender Systems, Decision Trees, K-Means, LDA, RFM-Segmentation, XGBoost in Python, R, and Scala.

Code snippets and solutions for the Introduction to Deep Learning and Neural Networks Course hosted in educative.io

🏷️ An e-commerce marketplace template. An online auction and shopping website for buying and selling a wide variety of goods and services worldwide.

NVTabular is a feature engineering and preprocessing library for tabular data designed to quickly and easily manipulate terabyte scale datasets used to train deep learning based recommender systems.

Code of the NeurIPS 2021 paper: Language and Visual Entity Relationship Graph for Agent Navigation

AAAI 2020 - ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations

supervised and semi-supervised image classification with self-supervision (Keras)

ECNU ICA seminar materials

Tutorials for Machine Learning on Graphs

🛍️RetailBox - eCommerce Recommender System using Machine Learning

Implementation of Barlow Twins paper

Subgraph Neural Networks (NeurIPS 2020)

AAAI'21: Data Augmentation for Graph Neural Networks

PyTorch implementation of EMAN for self-supervised and semi-supervised learning: https://arxiv.org/abs/2101.08482

Parametric Contrastive Learning (ICCV2021)

Self6D++: Occlusion-Aware Self-Supervised Monocular 6D Object Pose Estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) 2021.

Implementation of the paper "Certifiable Robustness and Robust Training for Graph Convolutional Networks".

(RecSys 2020) Adaptively Distilled Exemplar Replay towards Continual Learning for Session-based Recommendation [Best Short Paper]

Summary of social recommendation papers and codes

🔨 🍇 💻 🚀 GraphScope: A One-Stop Large-Scale Graph Computing System from Alibaba 来自阿里巴巴的一站式大规模图计算系统 图分析 图查询 图机器学习

Tensorflow Implementation for paper "self-supervised generative adversarial networks"

A spherical CNN for weather forecasting

A Tensorflow implementation of "Bayesian Graph Convolutional Neural Networks" (AAAI 2019).

Code for "Distributed, Egocentric Representations of Graphs for Detecting Critical Structures" (ICML 2019)

A github repository suggestion system

Pytorch differentiable molecular dynamics

Oh-My-Papers: a Hybrid Context-aware Paper Recommendation System

Context-Aware Visual Compatibility Prediction (https://arxiv.org/abs/1902.03646)

[ICLR 2021] How to Find Your Friendly Neighborhood: Graph Attention Design with Self-Supervision

a data science blog

PyTorch code for CVIU paper "AC-VRNN: Attentive Conditional-VRNN for Multi-Future Trajectory Prediction"