GCA
Source code for Graph Contrastive Learning with Adaptive Augmentation (WWW 2021)
For example, to run GCA-Degree under WikiCS, execute:
python train.py --device cuda:0 --dataset WikiCS --param local:wikics.json --drop_scheme degree
Source code for Graph Contrastive Learning with Adaptive Augmentation (WWW 2021)
For example, to run GCA-Degree under WikiCS, execute:
python train.py --device cuda:0 --dataset WikiCS --param local:wikics.json --drop_scheme degree
General purpose GPU compute framework for cross vendor graphics cards (AMD, Qualcomm, NVIDIA & friends). Blazing fast, mobile-enabled, asynchronous and optimized for advanced GPU data processing usec
GazeScroller Using Facial Movements to perform Hands-free Gesture on the system
ConvMixer ConvMixer, an extremely simple model that is similar in spirit to the ViT and the even-more-basic MLP-Mixer in that it operates directly on
SPLADE 🍴 + 🥄 = 🔎 This repository contains the weights for four models as well as the code for running inference for our two papers: [v1]: SPLADE: S
Multi-View Clustering Papers Collections for the lasted paper about multi-view clustering methods (papers, codes). There also exists some repositories
A Tensorflow implementation of the Text Conditioned Auxiliary Classifier Generative Adversarial Network for Generating Images from text descriptions
Knowledgeable Prompt-tuning: Incorporating Knowledge into Prompt Verbalizer for Text Classification
Automatic_Background_Remover A Web API for automatic background removal using Deep Learning. App is made using Flask and deployed on Heroku. 👉 https:
[ICCV 2021] A Simple Baseline for Semi-supervised Semantic Segmentation with Strong Data Augmentation
Continual learning with sketched Jacobian approximations This repository contains the code for reproducing figures and results in the paper ``Provable
Deepo is a series of Docker images that allows you to quickly set up your deep learning research environment supports almost all commonly used deep le
Pytorch library for end-to-end transformer models training and serving
Deduplicating Training Data Makes Language Models Better This repository contains code to deduplicate language model datasets as descrbed in the paper
Self-Blind-VSR Paper | Discussion Self-Supervised Deep Blind Video Super-Resolution By Haoran Bai and Jinshan Pan Abstract Existing deep learning-base
A GOOD REPRESENTATION DETECTS NOISY LABELS This code is a PyTorch implementation of the paper: Prerequisites Python 3.6.9 PyTorch 1.7.1 Torchvision 0.
BuildingNet This is the implementation of the BuildingNet architecture described in this paper: Paper: BuildingNet: Learning to Label 3D Buildings Arx
[CVPR 2022] Eigenlanes: Data-Driven Lane Descriptors for Structurally Diverse Lanes Dongkwon Jin, Wonhui Park, Seong-Gyun Jeong, Heeyeon Kwon, and Cha
Foolbox Native: Fast adversarial attacks to benchmark the robustness of machine learning models in PyTorch, TensorFlow, and JAX Foolbox is a Python li
Deeplab-resnet-101 Pytorch with Lovász hinge loss Train deeplab-resnet-101 with binary Jaccard loss surrogate, the Lovász hinge, as described in http:
Layer-wise Relevance Propagation (LRP) in PyTorch Basic unsupervised implementation of Layer-wise Relevance Propagation (Bach et al., Montavon et al.)