no code implementations • 20 Feb 2024 • Fei Wang, Ruohui Zhang, Chenglin Chen, Min Yang, Yun Bai
The prediction map determines whether an object is in a crowd, and we prioritize state estimations over observations when severe deformation of observations occurs, accomplished through the covariance adaptive Kalman filter.
no code implementations • 13 Sep 2023 • Yun Bai, Simon Camal, Andrea Michiorri
This paper proposes a Long and Short-Term Memory (LSTM) network incorporating textual news features that successfully predicts the deterministic and probabilistic tasks of the UK national electricity demand.
1 code implementation • 11 Jul 2023 • Yachuan Li, Zongmin Li, Xavier Soria P., Chaozhi Yang, Qian Xiao, Yun Bai, Hua Li, Xiangdong Wang
In this work, we propose a Compact Twice Fusion Network (CTFN) to fully integrate multi-scale features while maintaining the compactness of the model.
no code implementations • 18 Jan 2023 • Yun Bai, Simon Camal, Andrea Michiorri
This study explores the link between electricity demand and more nuanced information about social events.
1 code implementation • 6 Apr 2021 • Yun Bai, Ganglin Tian, Yanfei Kang, Suling Jia
It is also possible to improve the NCL ensemble with a regularization term in the objective function.
no code implementations • 28 Feb 2021 • Xixi Li, Yun Bai, Yanfei Kang
This paper aims to study the social influence of virtual community on user behaviors in the M5 competition.
no code implementations • 19 Jan 2020 • Yun Bai, Xixi Li, Hao Yu, Suling Jia
Sparse and short news headlines can be arbitrary, noisy, and ambiguous, making it difficult for classic topic model LDA (latent Dirichlet allocation) designed for accommodating long text to discover knowledge from them.
no code implementations • 1 Nov 2019 • Yun Bai, Suling Jia, Xixi Li
Based on the online transaction data of COSCO group's centralized procurement platform, this paper studies the clustering method of time series type data.
no code implementations • 19 Apr 2018 • Vernon Asuncion, Yan Zhang, Heng Zhang, Yun Bai, Weisheng Si
In particular, we prove that this language satisfies the so-called bounded derivation-depth prop- erty (BDDP), which implies that the CQA is first-order rewritable, and its data complexity is in AC0 .