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Fei Wang

Institute of Computing Technology, Chinese Academy of Sciences

7 papers hereh-index 244.8k citations60 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author4

Across the 4 of 7 papers where every author was matched, so the position is known.

fields
  • cs.LG4
  • cs.CV2
  • cs.AI1
affiliations
  • Institute of Computing Technology, Chinese Academy of Sciences
HomepageORCID 0000-0002-3282-0535
same name
  • Fei Wang — 33 papers, h 135
  • Fei Wang — 15 papers, h 7
  • Fei Wang — 13 papers, h 20
  • Fei Wang — 12 papers, h 4
  • Fei Wang — 11 papers, h 3
  • Fei Wang — 9 papers, h 3

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

collaborators
Showing cs.LGShow all

4 papers · 1 filter

cs.LG2025

HUTFormer: Hierarchical U-Net Transformer for Long-Term Traffic Forecasting

Zezhi Shao, Fei Wang, Tao Sun +7

Traffic forecasting, which aims to predict traffic conditions based on historical observations, has been an enduring research topic and is widely recognized as an essential compone…

cs.LG2025

On the Integration of Spatial-Temporal Knowledge: A Lightweight Approach to Atmospheric Time Series Forecasting

Yisong Fu, Fei Wang, Zezhi Shao +6

Transformers have gained attention in atmospheric time series forecasting (ATSF) for their ability to capture global spatial-temporal correlations. However, their complex architect…

cs.LG2024

Exploring Progress in Multivariate Time Series Forecasting: Comprehensive Benchmarking and Heterogeneity Analysis

Zezhi Shao, Fei Wang, Yongjun Xu +10

Multivariate Time Series (MTS) analysis is crucial to understanding and managing complex systems, such as traffic and energy systems, and a variety of approaches to MTS forecasting…

cs.LG2024

GinAR: An End-To-End Multivariate Time Series Forecasting Model Suitable for Variable Missing

Chengqing Yu, Fei Wang, Zezhi Shao +4

Multivariate time series forecasting (MTSF) is crucial for decision-making to precisely forecast the future values/trends, based on the complex relationships identified from histor…

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