52 Open source projects that are alternatives of or similar to GRACE

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

Code and resources on scalable and efficient Graph Neural Networks

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

Model-Contrastive Federated Learning (CVPR 2021)

Code for the paper "Contrastive Learning Inverts the Data Generating Process".

Experiments with supervised contrastive learning methods with different loss functions

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.

Pytorch implementation of "A Simple Framework for Contrastive Learning of Visual Representations"

[CIKM 2021] Enhancing Aspect-Based Sentiment Analysis with Supervised Contrastive Learning

VarCLR: Variable Semantic Representation Pre-training via Contrastive Learning

Source code for GNN-LSPE (Graph Neural Networks with Learnable Structural and Positional Representations), ICLR 2022

[EMNLP 2021] Mirror-BERT: Converting Pretrained Language Models to universal text encoders without labels.

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

List of Publications in Graph Contrastive Learning

Code for the RA-L (IROS) 2021 paper "A Hierarchical Dual Model of Environment- and Place-Specific Utility for Visual Place Recognition"

Quaternion Graph Neural Networks (ACML 2021) (Pytorch and Tensorflow)

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

CVC: Contrastive Learning for Non-parallel Voice Conversion (INTERSPEECH 2021, in PyTorch)

A curated list for awesome graph representation learning resources.

A curated list of awesome graph & self-supervised-learning-based recommendation.

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

Generalized Deep Metric Learning.

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

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

Official PyTorch implementation of Contrastive Learning of Musical Representations

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

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

Subgraph Neural Networks (NeurIPS 2020)

Parametric Contrastive Learning (ICCV2021)

PyTorch Implementation on Paper [CVPR2021]Distilling Audio-Visual Knowledge by Compositional Contrastive Learning

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

Graph Embedding via Frequent Subgraphs

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

Visualization tool for Graph Neural Networks

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

official implemntation for "Contrastive Learning with Stronger Augmentations"

Implementation for "3D human pose, shape and texture from low-resolution images and videos", TPAMI 2021

Implements the ideas presented in https://arxiv.org/pdf/2004.11362v1.pdf by Khosla et al.

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

[NeurIPS 2021] COCO-LM: Correcting and Contrasting Text Sequences for Language Model Pretraining

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

Code for EMNLP 2021 paper "Topic-Aware Contrastive Learning for Abstractive Dialogue Summarization"

Python library for Representation Learning on Knowledge Graphs https://docs.ampligraph.org

A collection of important graph embedding, classification and representation learning papers with implementations.

links to conference publications in graph-based deep learning

Inductive relation prediction by subgraph reasoning, ICML'20

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

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

Parametric Instance Classification for Unsupervised Visual Feature Learning, NeurIPS 2020

Official implementation for "Image Quality Assessment using Contrastive Learning"

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

The codebase for "Group-wise Contrastive Learning for Neural Dialogue Generation" (Cai et al., Findings of EMNLP 2020)