IEEE

DACAD: Domain Adaptation Contrastive Learning for Anomaly Detection in Multivariate Time Series

Abstract: In time series anomaly detection (TSAD), the scarcity of labeled data poses a challenge to the development of accurate models. Unsupervised domain adaptation (UDA) offers a solution by ...
GitHub

CTR-Gait: Semantic-Aware Contrastive Learning for Fine-Grained Gait Emotion Recognition

This repository contains the official PyTorch implementation of the paper: "CTR-Gait: Semantic-Aware Contrastive Learning for Fine-Grained Gait Emotion Recognition" (Submitted to IEEE Transactions on ...
GitHub

Learn PyTorch for Deep Learning

Welcome to the Zero to Mastery Learn PyTorch for Deep Learning course, the second best place to learn PyTorch on the internet (the first being the PyTorch documentation). 00 - PyTorch Fundamentals ...
IEEE

Simple Yet Effective Heterogeneous Graph Contrastive Learning for Recommendation

Abstract: Contrastive learning has emerged as a prominent approach in Heterogeneous Graph Neural Network (HGNN)-based recommender systems, exhibiting particular efficacy in addressing the sparsity ...