14 citations · 18 across the 8 of their papers we have counts for
8 papers
CVTN: Cross Variable and Temporal Integration for Time Series Forecasting
Han Zhou, Yuntian Chen
In multivariate time series forecasting, the Transformer architecture encounters two significant challenges: effectively mining features from historical sequences and avoiding over…
Bridging Data Barriers among Participants: Assessing the Potential of Geoenergy through Federated Learning
Weike Peng, Jiaxin Gao, Yuntian Chen +1
Machine learning algorithms emerge as a promising approach in energy fields, but its practical is hindered by data barriers, stemming from high collection costs and privacy concern…
Vision-Informed Flow Image Super-Resolution with Quaternion Spatial Modeling and Dynamic Flow Convolution
Qinglong Cao, Zhengqin Xu, Chao Ma +2
Flow image super-resolution (FISR) aims at recovering high-resolution turbulent velocity fields from low-resolution flow images. Existing FISR methods mainly process the flow image…
Empowering Machines to Think Like Chemists: Unveiling Molecular Structure-Polarity Relationships with Hierarchical Symbolic Regression
Siyu Lou, Chengchun Liu, Yuntian Chen +1
Thin-layer chromatography (TLC) is a crucial technique in molecular polarity analysis. Despite its importance, the interpretability of predictive models for TLC, especially those d…
Multi-spatial Multi-temporal Air Quality Forecasting with Integrated Monitoring and Reanalysis Data
Yuxiao Hu, Qian Li, Xiaodan Shi +2
Accurate air quality forecasting is crucial for public health, environmental monitoring and protection, and urban planning. However, existing methods fail to effectively utilize mu…
Reflection Invariance Learning for Few-shot Semantic Segmentation
Qinglong Cao, Yuntian Chen, Chao Ma +1
Few-shot semantic segmentation (FSS) aims to segment objects of unseen classes in query images with only a few annotated support images. Existing FSS algorithms typically focus on…