Convergence Analysis of Controlled Particle Systems Arising in Deep Learning: From Finite to Infinite Sample Size
- DOI
- 10.1007/s00245-026-10503-2
- Published
- 2026-09-10
- Container
- Applied Mathematics & Optimization
- Publisher
- Springer Science and Business Media LLC
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1007/s00245-026-10503-2,
title = {Convergence Analysis of Controlled Particle Systems Arising in Deep Learning: From Finite to Infinite Sample Size},
author = {Huafu Liao and Alpár R. Mészáros and Chenchen Mou and Chao Zhou},
year = {2026},
journal = {Applied Mathematics \& Optimization},
doi = {10.1007/s00245-026-10503-2},
url = {https://doi.org/10.1007/s00245-026-10503-2}
}RIS
TY - JOUR TI - Convergence Analysis of Controlled Particle Systems Arising in Deep Learning: From Finite to Infinite Sample Size AU - Huafu Liao AU - Alpár R. Mészáros AU - Chenchen Mou AU - Chao Zhou PY - 2026 JO - Applied Mathematics & Optimization DO - 10.1007/s00245-026-10503-2 UR - https://doi.org/10.1007/s00245-026-10503-2 ER -
APA
Liao, H., Mészáros, A. R., Mou, C., & Zhou, C. (2026). Convergence Analysis of Controlled Particle Systems Arising in Deep Learning: From Finite to Infinite Sample Size. Applied Mathematics & Optimization. https://doi.org/10.1007/s00245-026-10503-2
Source records
- crossref · retrieved 2026-09-25T11:07:33.132Z