Author

H. Owhadi

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Open access Oct 2026

Bridging Machine Learning and Algorithmic Information Theory, Part VII: Algorithmic Information Kernels and Kernel Discrepancies on Countable Spaces

Compression-based dissimilarities such as the normalized compression distance are widely used, but direct exponentiation need not produce a positive semidefinite kernel. We develop a systematic interface between prefix algorithmic information theory and three kernel discrepancy methods on finite or countable spaces: ma...

B. Hamzi, Marcus Hutter, H. Owhadi · Entropy · 0 citations

#machine learning May 2026

ISOMORPH: A Supply Chain Digital Twin for Simulation, Dataset Generation, and Forecasting Benchmarks

This work introduces ISOMORPH, the first public digital twin of a multi-echelon logistics network with interpretable, user-configurable parameters and modular topology, demand, and control rules, and introduces forecasting regimes that differ from standard real-world TSF benchmarks.

Zhizhen Zhang, Hyemin Gu, Benjamin J. Zhang et al. · arXiv.org · 0 citations

#machine learning Sep 2025

Data-efficient Kernel Methods for Learning Hamiltonian Systems

This work proposes kernel-based methods for identifying and forecasting Hamiltonian systems directly from trajectory data, and provides a more general, problem-agnostic numerical framework that goes beyond Hamiltonian systems and can be used for data-driven learning of arbitrary dynamical systems.

Yasamin Jalalian, Mostafa Samir, B. Hamzi et al. · arXiv.org · 4 citations