This is the repository for the AAAI 21 paper [Contrastive and Generative Graph Convolutional Networks for Graph-based Semi-Supervised Learning].

Related tags

Deep LearningCG3
Overview

CG3

This is the repository for the AAAI 21 paper [Contrastive and Generative Graph Convolutional Networks for Graph-based Semi-Supervised Learning].

Requirements

  • Tensorflow (1.14.0)

Usage

You can conduct node classification experiments on benchmark datasets (e.g., CiteSeer) by running the 'main.py' file.

Cite

Please cite our paper if you use this code in your own work:

@inproceedings{Wan2021Contrastive,
  title={Contrastive and Generative Graph Convolutional Networks for Graph-based Semi-Supervised Learning},
  author={Wan, Sheng and Pan, Shirui and Yang, Jian and Gong, Chen},
  booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
  volume={35},
  number={11},
  pages={10049-10057},
  year={2021}
}
Nicholas Lee 3 Jan 09, 2022
Semi-Supervised Semantic Segmentation with Pixel-Level Contrastive Learning from a Class-wise Memory Bank

This repository provides the official code for replicating experiments from the paper: Semi-Supervised Semantic Segmentation with Pixel-Level Contrast

Iñigo Alonso Ruiz 58 Dec 15, 2022
[ICCV 2021] Released code for Causal Attention for Unbiased Visual Recognition

CaaM This repo contains the codes of training our CaaM on NICO/ImageNet9 dataset. Due to my recent limited bandwidth, this codebase is still messy, wh

Wang Tan 66 Dec 31, 2022
Contains code for the paper "Vision Transformers are Robust Learners".

Vision Transformers are Robust Learners This repository contains the code for the paper Vision Transformers are Robust Learners by Sayak Paul* and Pin

Sayak Paul 103 Jan 05, 2023
Official PyTorch implementation of "Contrastive Learning from Extremely Augmented Skeleton Sequences for Self-supervised Action Recognition" in AAAI2022.

AimCLR This is an official PyTorch implementation of "Contrastive Learning from Extremely Augmented Skeleton Sequences for Self-supervised Action Reco

Gty 44 Dec 17, 2022
Multiple types of NN model optimization environments. It is possible to directly access the host PC GUI and the camera to verify the operation. Intel iHD GPU (iGPU) support. NVIDIA GPU (dGPU) support.

mtomo Multiple types of NN model optimization environments. It is possible to directly access the host PC GUI and the camera to verify the operation.

Katsuya Hyodo 24 Mar 02, 2022
PyTorch implementation of CloudWalk's recent work DenseBody

densebody_pytorch PyTorch implementation of CloudWalk's recent paper DenseBody. Note: For most recent updates, please check out the dev branch. Update

Lingbo Yang 401 Nov 19, 2022
This project is based on our SIGGRAPH 2021 paper, ROSEFusion: Random Optimization for Online DenSE Reconstruction under Fast Camera Motion .

ROSEFusion 🌹 This project is based on our SIGGRAPH 2021 paper, ROSEFusion: Random Optimization for Online DenSE Reconstruction under Fast Camera Moti

219 Dec 27, 2022
PyTorch implementation for Convolutional Networks with Adaptive Inference Graphs

Convolutional Networks with Adaptive Inference Graphs (ConvNet-AIG) This repository contains a PyTorch implementation of the paper Convolutional Netwo

Andreas Veit 176 Dec 07, 2022
Benchmarks for Model-Based Optimization

Design-Bench Design-Bench is a benchmarking framework for solving automatic design problems that involve choosing an input that maximizes a black-box

Brandon Trabucco 43 Dec 20, 2022
Misc YOLOL scripts for use in the Starbase space sandbox videogame

starbase-misc Misc YOLOL scripts for use in the Starbase space sandbox videogame. Each directory contains standalone YOLOL scripts. They don't really

4 Oct 17, 2021
Implements VQGAN+CLIP for image and video generation, and style transfers, based on text and image prompts. Emphasis on ease-of-use, documentation, and smooth video creation.

VQGAN-CLIP-GENERATOR Overview This is a package (with available notebook) for running VQGAN+CLIP locally, with a focus on ease of use, good documentat

Ryan Hamilton 98 Dec 30, 2022
A baseline code for VSPW

A baseline code for VSPW Preparation Download VSPW dataset The VSPW dataset with extracted frames and masks is available here.

28 Aug 22, 2022
Attack on Confidence Estimation algorithm from the paper "Disrupting Deep Uncertainty Estimation Without Harming Accuracy"

Attack on Confidence Estimation (ACE) This repository is the official implementation of "Disrupting Deep Uncertainty Estimation Without Harming Accura

3 Mar 30, 2022
A repo with study material, exercises, examples, etc for Devnet SPAUTO

MPLS in the SDN Era -- DevNet SPAUTO Get right to the study material: Checkout the Wiki! A lab topology based on MPLS in the SDN era book used for 30

Hugo Tinoco 67 Nov 16, 2022
This package implements the algorithms introduced in Smucler, Sapienza, and Rotnitzky (2020) to compute optimal adjustment sets in causal graphical models.

optimaladj: A library for computing optimal adjustment sets in causal graphical models This package implements the algorithms introduced in Smucler, S

Facundo Sapienza 6 Aug 04, 2022
Train/evaluate a Keras model, get metrics streamed to a dashboard in your browser.

Hera Train/evaluate a Keras model, get metrics streamed to a dashboard in your browser. Setting up Step 1. Plant the spy Install the package pip

Keplr 495 Dec 10, 2022
A Python framework for conversational search

Chatty Goose Multi-stage Conversational Passage Retrieval: An Approach to Fusing Term Importance Estimation and Neural Query Rewriting Installation Ma

Castorini 36 Oct 23, 2022
KinectFusion implemented in Python with PyTorch

KinectFusion implemented in Python with PyTorch This is a lightweight Python implementation of KinectFusion. All the core functions (TSDF volume, fram

Jingwen Wang 80 Jan 03, 2023
This repository provides an unified frameworks to train and test the state-of-the-art few-shot font generation (FFG) models.

FFG-benchmarks This repository provides an unified frameworks to train and test the state-of-the-art few-shot font generation (FFG) models. What is Fe

Clova AI Research 101 Dec 27, 2022