Jianglin954

PR-2021-LRAGE-Codes

[PR 2021] Low-Rank Adaptive Graph Embedding for Unsupervised Feature Extraction

ALBEF

Code for ALBEF: a new vision-language pre-training method

Awesome-Diffusion-Models

A collection of resources and papers on Diffusion Models and Score-based Models, a darkhorse in the field of Generative Models

Awesome-Graph-Neural-Networks

Paper Lists for Graph Neural Networks

awesome-graph-transformer

Papers about graph transformers.

Awesome-HDR

Collect High Dynamic Range Imaging Related Papers and Codes

Awesome-Learning-with-Label-Noise

A curated list of resources for Learning with Noisy Labels

awesome-phd-advice

Collection of advice for prospective and current PhD students

awesome-vision-language-pretraining-papers

Recent Advances in Vision and Language PreTrained Models (VL-PTMs)

benchmarking-gnns

Repository for benchmarking graph neural networks

cogdl

CogDL: An Extensive Toolkit for Deep Learning on Graphs (Graph Neural Networks, GNN)

DALLE-pytorch

Implementation / replication of DALL-E, OpenAI's Text to Image Transformer, in Pytorch

deep_gcns_torch

Pytorch Repo for DeepGCNs (ICCV'2019 Oral, TPAMI'2021), DeeperGCN (arXiv'2020) and GNN1000(ICML'2021): https://www.deepgcns.org

dgcnn

DGM_pytorch

Efficient-AI-Backbones

Efficient AI Backbones including GhostNet, TNT and MLP, developed by Huawei Noah's Ark Lab.

GraphGym

Platform for designing and evaluating Graph Neural Networks (GNN)

GraphMAE

GraphMAE: Self-Supervised Masked Graph Autoencoders in KDD'22

ICPR-2020-LSAH-Codes

Source Code for "Label Self-Adaption Hashing for Image Retrieval". International Conference on Pattern Recognition (ICPR), 2020.

INS-2021-RLRRP-Codes

Source Code for "Target Redirected Regression with Dynamic Neighborhood Structure". Information Sciences, 2021.

Large_Scale_GCN_Benchmarking

This is an authors' implementation of the NIPS 2022 dataset and Benchmark Track Paper "A Comprehensive Study on Large Scale Graph Training: Benchmarking and Rethinking" in PyTorch.

Low-Level-Vision-Paper-Record

记录近期的 1) 图像/视频的超分增强等low level vision任务; 2) 图像生成 等任务相关论文, 主要为18年以后的DL based方法.

PaddleViT

:robot: PaddleViT: State-of-the-art Visual Transformer and MLP Models for PaddlePaddle 2.0+

pyGAT

Pytorch implementation of the Graph Attention Network model by Veličković et. al (2017, https://arxiv.org/abs/1710.10903)

pytorch-loss

label-smooth, amsoftmax, partial-fc, focal-loss, triplet-loss, lovasz-softmax. Maybe useful

Simplifying-Clustering-with-Graph-Neural-Networks

Tensorflow and Pytorch implementation of "Just Balance GNN" for graph clustering.

TNNLS-2022-GER-Codes

[TNNLS 2022] Generalized Embedding Regression: A Framework for Supervised Feature Extraction

awesome-graph-attack-papers

Adversarial attacks and defenses on Graph Neural Networks.

DeepRobust

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

IDGL

Code & data accompanying the NeurIPS 2020 paper "Iterative Deep Graph Learning for Graph Neural Networks: Better and Robust Node Embeddings".