TESTAM: A Time-Enhanced Spatio-Temporal Attention Model with Mixture of Experts

5 March 2024

Papers citing "TESTAM: A Time-Enhanced Spatio-Temporal Attention Model with Mixture of Experts"

5 / 5 papers shown

Title
MoGERNN: An Inductive Traffic Predictor for Unobserved Locations in Dynamic Sensing Networks Qishen Zhou Yifan Zhang Michail A. Makridis Anastasios Kouvelas Yibing Wang Simon Hu AI4TS 75 1 0 21 Jan 2025
HiMoE: Heterogeneity-Informed Mixture-of-Experts for Fair Spatial-Temporal Forecasting Shaohan Yu Pan Deng Yu Zhao J. Liu Ziáng Wang MoE 140 0 0 30 Nov 2024
FACTS: A Factored State-Space Framework For World Modelling Li Nanbo Firas Laakom Yucheng Xu Wenyi Wang Jürgen Schmidhuber AI4TS 104 0 0 28 Oct 2024
Mixture-of-Experts with Expert Choice Routing Yan-Quan Zhou Tao Lei Han-Chu Liu Nan Du Yanping Huang Vincent Zhao Andrew M. Dai Zhifeng Chen Quoc V. Le James Laudon MoE 149 327 0 18 Feb 2022
Discrete Graph Structure Learning for Forecasting Multiple Time Series Chao Shang Jie Chen J. Bi CML BDL AI4TS 94 11 0 18 Jan 2021