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09/20/2023
Potential and limitations of random Fourier features for dequantizing quantum machine learning
Quantum machine learning is arguably one of the most explored applicatio...
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05/31/2023
Shadows of quantum machine learning
Quantum machine learning is often highlighted as one of the most promisi...
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03/22/2023
The power and limitations of learning quantum dynamics incoherently
Quantum process learning is emerging as an important tool to study quant...
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12/19/2022
Quantum policy gradient algorithms
Understanding the power and limitations of quantum access to data in mac...
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07/13/2022
Reinforcement Learning Assisted Recursive QAOA
Variational quantum algorithms such as the Quantum Approximation Optimiz...
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11/18/2021
Near-Optimal Quantum Algorithms for Multivariate Mean Estimation
We propose the first near-optimal quantum algorithm for estimating in Eu...
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10/25/2021
Quantum machine learning beyond kernel methods
With noisy intermediate-scale quantum computers showing great promise fo...
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03/09/2021
Variational quantum policies for reinforcement learning
Variational quantum circuits have recently gained popularity as quantum ...
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01/02/2020
Operationally meaningful representations of physical systems in neural networks
To make progress in science, we often build abstract representations of ...
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10/28/2019
A framework for deep energy-based reinforcement learning with quantum speed-up
In the past decade, deep learning methods have seen tremendous success i...
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07/17/2019