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20122020
most citedQuantum Machine Learning

4.7k citations · 6.4k across the 32 of their papers we have counts for

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16 papers · 1 filter

quant-ph2020★ 11 cited

Defence against adversarial attacks using classical and quantum-enhanced Boltzmann machines

Aidan Kehoe, Peter Wittek, Yanbo Xue +1

We provide a robust defence to adversarial attacks on discriminative algorithms. Neural networks are naturally vulnerable to small, tailored perturbations in the input data that le…

quant-ph2019

An Artificial Spiking Quantum Neuron

Lasse Bjørn Kristensen, Matthias Degroote, Peter Wittek +2

Artificial spiking neural networks have found applications in areas where the temporal nature of activation offers an advantage, such as time series prediction and signal processin…

quant-ph2019★ 82 cited

Vulnerability of quantum classification to adversarial perturbations

Nana Liu, Peter Wittek

High-dimensional quantum systems are vital for quantum technologies and are essential in demonstrating practical quantum advantage in quantum computing, simulation and sensing. Sin…

quant-ph2018★ 187 cited

Open source software in quantum computing

Mark Fingerhuth, Tomáš Babej, Peter Wittek

Open source software is becoming crucial in the design and testing of quantum algorithms. Many of the tools are backed by major commercial vendors with the goal to make it easier t…

quant-ph2018★ 2 cited

Evaluating probabilistic programming languages for simulating quantum correlations

Abdul Obeid, Peter D. Bruza, Peter Wittek

This article explores how probabilistic programming can be used to simulate quantum correlations in an EPR experimental setting. Probabilistic programs are based on standard probab…

quant-ph2018★ 7 cited

Verifying the output of quantum optimizers with ground-state energy lower bounds

Flavio Baccari, Christian Gogolin, Peter Wittek +1

Solving optimisation problems encoded in the ground state of classical-spin systems is a focus area for quantum computing devices, providing upper bounds to the unknown solution. T…

quant-ph2018★ 62 cited

Bayesian Deep Learning on a Quantum Computer

Zhikuan Zhao, Alejandro Pozas-Kerstjens, Patrick Rebentrost +1

Bayesian methods in machine learning, such as Gaussian processes, have great advantages com-pared to other techniques. In particular, they provide estimates of the uncertainty asso…

quant-ph2018★ 50 cited

Automated discovery of characteristic features of phase transitions in many-body localization

Patrick Huembeli, Alexandre Dauphin, Peter Wittek +1

We identify a new "order parameter" for the disorder driven many-body localization (MBL) transition by leveraging artificial intelligence. This allows us to pin down the transition…

quant-ph2018★ 1 cited

Entangled systems are unbounded sources of nonlocal correlations and of certified random numbers

Florian J. Curchod, Markus Johansson, Remigiusz Augusiak +3

The outcomes of local measurements made on entangled systems can be certified to be random provided that the generated statistics violate a Bell inequality. This way of producing r…

quant-ph2016★ 43 cited

Efficient device-independent entanglement detection for multipartite systems

Flavio Baccari, Daniel Cavalcanti, Peter Wittek +1

Entanglement is one of the most studied properties of quantum mechanics for its application in quantum information protocols. Nevertheless, detecting the presence of entanglement i…

quant-ph2016★ 4.7k cited

Quantum Machine Learning

Jacob Biamonte, Peter Wittek, Nicola Pancotti +3

Fuelled by increasing computer power and algorithmic advances, machine learning techniques have become powerful tools for finding patterns in data. Since quantum systems produce co…

quant-ph2016★ 180 cited

Simulating positive-operator-valued measures with projective measurements

Michał Oszmaniec, Leonardo Guerini, Peter Wittek +1

Standard projective measurements represent a subset of all possible measurements in quantum physics, defined by positive-operator-valued measures. We study what quantum measurement…

quant-ph2016★ 2 cited

Single-shot Adaptive Measurement for Quantum-enhanced Metrology

Pantita Palittapongarnpim, Peter Wittek, Barry C. Sanders

Quantum-enhanced metrology aims to estimate an unknown parameter such that the precision scales better than the shot-noise bound. Single-shot adaptive quantum-enhanced metrology (A…

quant-ph2016★ 90 cited

Bell inequalities tailored to maximally entangled states

Alexia Salavrakos, Remigiusz Augusiak, Jordi Tura +3

Bell inequalities have traditionally been used to demonstrate that quantum theory is nonlocal, in the sense that there exist correlations generated from composite quantum states th…

quant-ph2015★ 146 cited

Unbounded randomness certification using sequences of measurements

F. J. Curchod, M. Johansson, R. Augusiak +3

Unpredictability, or randomness, of the outcomes of measurements made on an entangled state can be certified provided that the statistics violate a Bell inequality. In the standard…

quant-ph2015★ 143 cited

Optimal randomness certification from one entangled bit

Antonio Acín, Stefano Pironio, Tamás Vértesi +1

By performing local projective measurements on a two-qubit entangled state one can certify in a device-independent way up to one bit of randomness. We show here that general measur…