221 citations · 602 across the 23 of their papers we have counts for
4 papers · 1 filter
On fundamental aspects of quantum extreme learning machines
Weijie Xiong, Giorgio Facelli, Mehrad Sahebi +4
Quantum Extreme Learning Machines (QELMs) have emerged as a promising framework for quantum machine learning. Their appeal lies in the rich feature map induced by the dynamics of a…
Does provable absence of barren plateaus imply classical simulability?
M. Cerezo, Martin Larocca, Diego García-Martín +9
A large amount of effort has recently been put into understanding the barren plateau phenomenon. In this perspective article, we face the increasingly loud elephant in the room and…
A Unified Framework for Trace-induced Quantum Kernels
Beng Yee Gan, Daniel Leykam, Supanut Thanasilp
Quantum kernel methods are promising candidates for achieving a practical quantum advantage for certain machine learning tasks. Similar to classical machine learning, an exact form…
Trainability barriers and opportunities in quantum generative modeling
Manuel S. Rudolph, Sacha Lerch, Supanut Thanasilp +5
Quantum generative models provide inherently efficient sampling strategies and thus show promise for achieving an advantage using quantum hardware. In this work, we investigate the…