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Behnoush Khavari

2 accepted papers

2026

The Expressive Limits of Diagonal SSMs for State-Tracking

ICLR 2026poster

State-Space Models (SSMs) have recently been shown to achieve strong empirical performance on a variety of long-range sequence modeling tasks while remaining efficient and highly-parallelizable. However, the theoretical understanding of their expressive power remains limited. In this work, we study…

Cited by 0SourceScholar
2021

Lower and Upper Bounds on the Pseudo-Dimension of Tensor Network Models

NeurIPS 2021spotlight

Tensor network methods have been a key ingredient of advances in condensed matter physics and have recently sparked interest in the machine learning community for their ability to compactly represent very high-dimensional objects. Tensor network methods can for example be used to efficiently learn l…

Cited by 11SourcePDFScholar