Author

S. Güttel

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Preprint Oct 2026

Fast matrix-vector products in tensor-train format via structured sketching

We propose a randomized, streamable algorithm that computes a tensor-train approximation of a matrix-vector product without ever forming the full intermediate tensor. We develop three contraction strategies for streaming tensor-train approximation (STTA): sequential, fused, and pre-sketched. We focus on the regime of l...

Alberto Bucci, S. Güttel, J. Pearson · 0 citations

Preprint Sep 2026

Integral chemical reaction neural networks

Discovering the structure and kinetics of chemical reaction networks (CRNs) from time-series concentration data is a fundamental challenge in chemical kinetics, with existing approaches relying on prior mechanistic assumptions or suffering from high computational cost and noise sensitivity. In this work, we present int...

Abraham Reyes-Velazquez, S. Güttel · 0 citations

#artificial intelligence Preprint Sep 2026

ROTE: Benchmarking Neural Memorization on Complexity-Controlled Symbolic Sequences

The study establishes a connection between the complexity of algorithmic sequences and the memorization capacity of neural architectures, revealing the trade-offs involving memorization quality, rollout stability, and computational expense.

Xin-Ye Chen, S. Güttel, Mohammad Mozaffari · 0 citations