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20182021
most citedThe Inductive Bias of Quantum Kernels

6 citations · 6 across the 1 of their papers we have counts for

collaborators

5 papers

quant-ph20216 cited

The Inductive Bias of Quantum Kernels

Jonas M. Kübler, Simon Buchholz, Bernhard Schölkopf

It has been hypothesized that quantum computers may lend themselves well to applications in machine learning. In the present work, we analyze function classes defined via quantum k…

math.ST2020

Kernel Conditional Moment Test via Maximum Moment Restriction

Krikamol Muandet, Wittawat Jitkrittum, Jonas Kübler

We propose a new family of specification tests called kernel conditional moment (KCM) tests. Our tests are built on a novel representation of conditional moment restrictions in a r…

quant-ph2019

An Adaptive Optimizer for Measurement-Frugal Variational Algorithms

Jonas M. Kübler, Andrew Arrasmith, Lukasz Cincio +1

Variational hybrid quantum-classical algorithms (VHQCAs) have the potential to be useful in the era of near-term quantum computing. However, recently there has been concern regardi…

quant-ph2019

Quantum Mean Embedding of Probability Distributions

Jonas M. Kübler, Krikamol Muandet, Bernhard Schölkopf

The kernel mean embedding of probability distributions is commonly used in machine learning as an injective mapping from distributions to functions in an infinite dimensional Hilbe…

quant-ph2018

Two-qubit causal structures and the geometry of positive qubit-maps

Jonas Kübler, Daniel Braun

We study quantum causal inference in a set-up proposed by Ried et al. [Nat. Phys. 11, 414 (2015)] in which a common-cause scenario can be mixed with a cause-effect scenario, and fo…