no code implementations • 14 May 2024 • Qinshuo Liu, Yanwen Fang, PengTao Jiang, Guodong Li
Multivariate time series forecasting tasks are usually conducted in a channel-dependent (CD) way since it can incorporate more variable-relevant information.
1 code implementation • ICLR 2023 • Jintai Chen, Kuanlun Liao, Yanwen Fang, Danny Chen, Jian Wu
In this paper, we propose to encapsulate all feature values of a record into vectorial features and process them collectively rather than have to deal with individual ones, which directly captures the representations at the data level and benefits robust performances.
no code implementations • 6 Jun 2023 • Yanwen Fang, Jintai Chen, Peng-Tao Jiang, Chao Li, Yifeng Geng, Eddy K. F. LAM, Guodong Li
Multi-person motion prediction is a challenging task, especially for real-world scenarios of highly interacted persons.
1 code implementation • 8 Feb 2023 • Yanwen Fang, Yuxi Cai, Jintai Chen, Jingyu Zhao, Guangjian Tian, Guodong Li
Motivated by this, we devise a cross-layer attention mechanism, called multi-head recurrent layer attention (MRLA), that sends a query representation of the current layer to all previous layers to retrieve query-related information from different levels of receptive fields.
1 code implementation • 17 Nov 2022 • Yuxuan Zhou, Zhi-Qi Cheng, Chao Li, Yanwen Fang, Yifeng Geng, Xuansong Xie, Margret Keuper
Skeleton-based action recognition aims to recognize human actions given human joint coordinates with skeletal interconnections.
Ranked #7 on Skeleton Based Action Recognition on NTU RGB+D 120
1 code implementation • NeurIPS 2021 • Jingyu Zhao, Yanwen Fang, Guodong Li
This paper introduces a concept of layer aggregation to describe how information from previous layers can be reused to better extract features at the current layer.
no code implementations • 24 Jul 2021 • Wenming Cao, Philip L. H. Yu, Gilbert C. S. Lui, Keith W. H. Chiu, Ho-Ming Cheng, Yanwen Fang, Man-Fung Yuen, Wai-Kay Seto
In this work, we propose a new segmentation network by integrating DenseUNet and bidirectional LSTM together with attention mechanism, termed as DA-BDense-UNet.
no code implementations • 22 Jul 2021 • Yanwen Fang, Philip L. H. Yu, Yaohua Tang
It is well known that modeling and forecasting realized covariance matrices of asset returns play a crucial role in the field of finance.