126 Open source projects that are alternatives of or similar to DIG

FisheyeDistanceNet

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

A paper list of research about social knowledge graph

MultiGraphGAN for predicting multiple target graphs from a source graph using geometric deep learning.

Explaining the output of machine learning models with more accurately estimated Shapley values

Graph Convolutional Networks, Graph Attention Networks, Gated Graph Neural Net, Mixhop

hypergraph representation learning, graph neural network

Federated learning on graph, especially on graph neural networks (GNNs), knowledge graph, and private GNN.

Create interactive dashboards for your Convolutional Neural Networks with a single line of code!

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

List of Publications in Graph Contrastive Learning

Interesting resources related to Explainable Artificial Intelligence, Interpretable Machine Learning, Interactive Machine Learning, Human in Loop and Visual Analytics.

PASSL包含 SimCLR，MoCo v1/v2，BYOL，CLIP，PixPro，BEiT，MAE等图像自监督算法以及 Vision Transformer，DEiT，Swin Transformer，CvT，T2T-ViT，MLP-Mixer，XCiT，ConvNeXt，PVTv2 等基础视觉算法

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).

A TensorFlow 2.x implementation of Masked Autoencoders Are Scalable Vision Learners

Neural Relation Understanding: neural cardinality estimators for tabular data

A Fast Knowledge Distillation Framework for Visual Recognition

Smart contract vulnerability detection using graph neural network (DR-GCN).

Variants of Vision Transformer and its downstream tasks

official implemntation for "Contrastive Learning with Stronger Augmentations"

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

Code and dataset of ACL2019 Paper: Graph Neural Networks with Generated Parameters for Relation Extraction.

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

[CVPR 2020] Action Segmentation with Joint Self-Supervised Temporal Domain Adaptation (PyTorch)

Code for our ACML and INTERSPEECH papers: "Speaker Diarization as a Fully Online Bandit Learning Problem in MiniVox".

[ICRA 2020] Train generalizable policies for kit assembly with self-supervised dense correspondence learning.

Generalized Deep Metric Learning.

毕业设计：基于图神经网络的异构图表示学习和推荐算法研究

A comprehensive list of awesome contrastive self-supervised learning papers.

A curated list of awesome machine learning interpretability resources.

OpenMMLab Self-Supervised Learning Toolbox and Benchmark

Fit interpretable models. Explain blackbox machine learning.

The code for our IEEE ACCESS (2020) paper Multimodal Emotion Recognition with Transformer-Based Self Supervised Feature Fusion.

Sample use case for Xavier AI in Healthcare conference: https://www.xavierhealth.org/ai-summit-day2/

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

GAM (Global Attribution Mapping) explains the landscape of neural network predictions across subpopulations

(Minimally) implements SimCLR (https://arxiv.org/abs/2002.05709) in TensorFlow 2.

Fast approximate Shapley values in R

🔧 Python Random Graph Generator

An unsupervised learning framework for depth and ego-motion estimation from monocular videos

Bootstrap Your Own Latent: A New Approach to Self-Supervised Learning

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

Implementation of E(n)-Equivariant Graph Neural Networks, in Pytorch

Tensorflow implementation of Learning Topology from Synthetic Data for Unsupervised Depth Completion (RAL 2021 & ICRA 2021)

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

Official codes: Self-Supervised Learning by Estimating Twin Class Distribution

A library for graph analysis written Julia.

Detect (classify and localize) people, pets and objects using millimeter-wave radar.

The official PyTorch implementation of "Pathfinder Discovery Networks for Neural Message Passing" (WebConf '21)

Parametric Instance Classification for Unsupervised Visual Feature Learning, NeurIPS 2020

This project provides responsible AI user interfaces for Fairlearn, interpret-community, and Error Analysis, as well as foundational building blocks that they rely on.

Code for paper "Can contrastive learning avoid shortcut solutions?" NeurIPS 2021.

An optimized graphs package for the Julia programming language

Official PyTorch implementation of Contrastive Learning of Musical Representations

Official project website for the CVPR 2021 paper "Exploring intermediate representation for monocular vehicle pose estimation"

Official code of "Towards Multi-Grained Explainability for Graph Neural Networks" (2021 NeurIPS)

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

Pytorch Lightning Implementation of SC-Depth (V1, V2...) for Unsupervised Monocular Depth Estimation.

Official code for "Mean Shift for Self-Supervised Learning"

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