Author

A. Kouvelas

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#machine learning Preprint Oct 2026

Sample-Efficiency of Kolmogorov-Arnold Networks

Deep reinforcement learning has achieved substantial performance gains over classical control approaches. Yet, a central challenge to learning in real-world applications is acquiring costly samples. Kolmogorov-Arnold Networks are a recently proposed architecture that can learn physical relationships in control problems...

Kevin Riehl, Shaimaa K. El-Baklish, Fan Wu et al. · 0 citations

#machine learning Preprint Sep 2026

Spatio-temporally complementary feature propagation on graphs for longitudinal AADT estimation

A novel spatio-temporally complementary feature propagation framework that leverages the strengths of two distinct data sources: spatially sparse but temporally dense loop detector data, and a spatially complete but temporally sparse macroscopic transportation model is proposed.

Ling-Hang Sun, Qi-Shen Zhou, M. Makridis et al. · 0 citations