GitHub

This is the official PyTorch implementation of our paper "Grad-PU: Arbitrary-Scale Point Cloud Upsampling via Gradient Descent with Learned Distance Functions" (CVPR 2023).

Most existing point cloud upsampling methods have roughly three steps: feature extraction, feature expansion and 3D coordinate prediction. However, they usually suffer from two critical issues: (1) ...
IEEE

A Survey on Graph Neural Networks for Time Series: Forecasting, Classification, Imputation, and Anomaly Detection

Abstract: Time series are the primary data type used to record dynamic system measurements and generated in great volume by both physical sensors and online processes (virtual sensors). Time series ...
IEEE

Dynamic Graph Neural Networks for Sequential Recommendation

Abstract: Modeling user preference from his historical sequences is one of the core problems of sequential recommendation. Existing methods in this field are widely distributed from conventional ...
GitHub

Knowledge graph-enhanced molecular contrastive learning with functional prompt

This repository is the official implementation of KANO, which is model proposed in a paper: Knowledge graph-enhanced molecular contrastive learning with functional prompt. Firstly, we construct a ...