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The effect of data encoding on the expressive power of variational quantum machine learning models
Maria Schuld, Ryan Sweke, Johannes Jakob Meyer
Quantum computers can be used for supervised learning by treating parametrised quantum circuits as models that map data inputs to predictions. While a lot of work has been done to…
On the Quantum versus Classical Learnability of Discrete Distributions
Ryan Sweke, Jean-Pierre Seifert, Dominik Hangleiter +1
Here we study the comparative power of classical and quantum learners for generative modelling within the Probably Approximately Correct (PAC) framework. More specifically we consi…
Tensor network approaches for learning non-linear dynamical laws
A. Goeßmann, M. Götte, I. Roth +3
Given observations of a physical system, identifying the underlying non-linear governing equation is a fundamental task, necessary both for gaining understanding and generating det…