activity
20212026
most citedHighAir: A Hierarchical Graph Neural Network-Based Air Quality Forecasting Method

22 citations · 22 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL2026

mHC: Manifold-Constrained Hyper-Connections

Zhenda Xie, Yixuan Wei, Huanqi Cao +17

Recently, studies exemplified by Hyper-Connections (HC) have extended the ubiquitous residual connection paradigm established over the past decade by expanding the residual stream…

cs.LG2025

Air Quality Prediction with A Meteorology-Guided Modality-Decoupled Spatio-Temporal Network

Hang Yin, Yan-Ming Zhang, Jian Xu +3

Air quality prediction plays a crucial role in public health and environmental protection. Accurate air quality prediction is a complex multivariate spatiotemporal problem, that in…

cs.CV2024

PCoTTA: Continual Test-Time Adaptation for Multi-Task Point Cloud Understanding

Jincen Jiang, Qianyu Zhou, Yuhang Li +6

In this paper, we present PCoTTA, an innovative, pioneering framework for Continual Test-Time Adaptation (CoTTA) in multi-task point cloud understanding, enhancing the model's tran…

cs.CV2024

DG-PIC: Domain Generalized Point-In-Context Learning for Point Cloud Understanding

Jincen Jiang, Qianyu Zhou, Yuhang Li +5

Recent point cloud understanding research suffers from performance drops on unseen data, due to the distribution shifts across different domains. While recent studies use Domain Ge…

cs.LG2021★ 22 cited

HighAir: A Hierarchical Graph Neural Network-Based Air Quality Forecasting Method

Ling Chen, Jiahui Xu, Binqing Wu +4

Accurately forecasting air quality is critical to protecting general public from lung and heart diseases. This is a challenging task due to the complicated interactions among disti…