Sparse Variational Student-t Processes for Heavy-Tailed Modeling
- DOI
- 10.1109/tnnls.2026.3673350
- Published
- 2026-09
- Container
- IEEE Transactions on Neural Networks and Learning Systems
- Publisher
- Institute of Electrical and Electronics Engineers (IEEE)
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1109/tnnls.2026.3673350,
title = {Sparse Variational Student-t Processes for Heavy-Tailed Modeling},
author = {Jian Xu and Delu Zeng and John Paisley},
year = {2026},
journal = {IEEE Transactions on Neural Networks and Learning Systems},
doi = {10.1109/tnnls.2026.3673350},
url = {https://doi.org/10.1109/tnnls.2026.3673350}
}RIS
TY - JOUR TI - Sparse Variational Student-t Processes for Heavy-Tailed Modeling AU - Jian Xu AU - Delu Zeng AU - John Paisley PY - 2026 JO - IEEE Transactions on Neural Networks and Learning Systems DO - 10.1109/tnnls.2026.3673350 UR - https://doi.org/10.1109/tnnls.2026.3673350 ER -
APA
Xu, J., Zeng, D., & Paisley, J. (2026). Sparse Variational Student-t Processes for Heavy-Tailed Modeling. IEEE Transactions on Neural Networks and Learning Systems. https://doi.org/10.1109/tnnls.2026.3673350
Source records
- crossref · retrieved 2026-09-26T15:53:45.605Z