Dynamic Autoregressive Tensor Factorization for Pattern Discovery of Spatiotemporal Systems.
- DOI
- 10.1109/tpami.2025.3576719
- Published
- 2025 Oct
- Container
- IEEE transactions on pattern analysis and machine intelligence
- Publisher
- Not recorded
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1109/tpami.2025.3576719,
title = {Dynamic Autoregressive Tensor Factorization for Pattern Discovery of Spatiotemporal Systems.},
author = {Chen X and Zhuang D and Cai H and Wang S and Zhao J},
year = {2025},
journal = {IEEE transactions on pattern analysis and machine intelligence},
doi = {10.1109/tpami.2025.3576719},
url = {https://doi.org/10.1109/tpami.2025.3576719}
}RIS
TY - JOUR TI - Dynamic Autoregressive Tensor Factorization for Pattern Discovery of Spatiotemporal Systems. AU - Chen X AU - Zhuang D AU - Cai H AU - Wang S AU - Zhao J PY - 2025 JO - IEEE transactions on pattern analysis and machine intelligence DO - 10.1109/tpami.2025.3576719 UR - https://doi.org/10.1109/tpami.2025.3576719 ER -
APA
X, C., D, Z., H, C., S, W., & J, Z. (2025). Dynamic Autoregressive Tensor Factorization for Pattern Discovery of Spatiotemporal Systems.. IEEE transactions on pattern analysis and machine intelligence. https://doi.org/10.1109/tpami.2025.3576719
Source records
- pubmed · retrieved 2026-09-25T22:39:06.801Z