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Heterogeneity-Informed Meta-Parameter Learning for Spatiotemporal Time Series Forecasting.

, , , , , , и . KDD, стр. 631-641. ACM, (2024)

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Jinliang Gao

Jinliang Yuan

Jinliang Zhuang

Jinliang Huang

Zhiguo Deng

 

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TTS-Norm: Forecasting Tensor Time Series via Multi-Way Normalization., , , , и . ACM Trans. Knowl. Discov. Data, 18 (1): 3:1-3:25 (января 2024)Learning Structured Components: Towards Modular and Interpretable Multivariate Time Series Forecasting., , , , , , и . CoRR, (2023)Heterogeneity-Informed Meta-Parameter Learning for Spatiotemporal Time Series Forecasting., , , , , , и . KDD, стр. 631-641. ACM, (2024)The Bigger the Better? Rethinking the Effective Model Scale in Long-term Time Series Forecasting., , , и . CoRR, (2024)Enhancing Spatio-temporal Quantile Forecasting with Curriculum Learning: Lessons Learned., , , , , , , , и . CoRR, (2024)A Multi-View Multi-Task Learning Framework for Multi-Variate Time Series Forecasting., , , , и . IEEE Trans. Knowl. Data Eng., 35 (8): 7665-7680 (августа 2023)Spatio-Temporal Adaptive Embedding Makes Vanilla Transformer SOTA for Traffic Forecasting., , , , , , и . CIKM, стр. 4125-4129. ACM, (2023)A Multi-view Multi-task Learning Framework for Multi-variate Time Series Forecasting., , , , и . CoRR, (2021)Gotta: Generative Few-shot Question Answering by Prompt-based Cloze Data Augmentation., , , , и . SDM, стр. 909-917. SIAM, (2023)Learning Gaussian Mixture Representations for Tensor Time Series Forecasting., , , и . IJCAI, стр. 2077-2085. ijcai.org, (2023)