| Quantum machine learning in feature Hilbert spaces M Schuld, N Killoran Physical review letters 122 (4), 040504, 2019 | 188 | 2019 |
| Converting non-classicality into entanglement N Killoran, FES Steinhoff, MB Plenio Physical Review Letters 116, 080402, 2016 | 145 | 2016 |
| Extracting entanglement from identical particles N Killoran, M Cramer, MB Plenio Physical Review Letters 112, 150501, 2014 | 121 | 2014 |
| Evaluating analytic gradients on quantum hardware M Schuld, V Bergholm, C Gogolin, J Izaac, N Killoran Physical Review A 99 (3), 032331, 2019 | 99 | 2019 |
| Resource theory of superposition T Theurer, N Killoran, D Egloff, MB Plenio Physical review letters 119 (23), 230401, 2017 | 84 | 2017 |
| Atmospheric continuous-variable quantum communication B Heim, C Peuntinger, N Killoran, I Khan, C Wittmann, C Marquardt, ... New Journal of Physics 16, 113018, 2014 | 82 | 2014 |
| Continuous-variable quantum neural networks N Killoran, TR Bromley, JM Arrazola, M Schuld, N Quesada, S Lloyd Physical Review Research 1 (3), 033063, 2019 | 80 | 2019 |
| Quantum generative adversarial networks PL Dallaire-Demers, N Killoran Physical Review A 98 (1), 012324, 2018 | 77 | 2018 |
| Strawberry fields: A software platform for photonic quantum computing N Killoran, J Izaac, N Quesada, V Bergholm, M Amy, C Weedbrook Quantum 3, 129, 2019 | 75 | 2019 |
| Enhancing light-harvesting power with coherent vibrational interactions: A quantum heat engine picture N Killoran, SF Huelga, MB Plenio The Journal of Chemical Physics 143, 155102, 2015 | 74 | 2015 |
| Coherent control of quantum systems as a resource theory JM Matera, D Egloff, N Killoran, MB Plenio Quantum Science and Technology 1 (1), 01LT01, 2016 | 61 | 2016 |
| Pennylane: Automatic differentiation of hybrid quantum-classical computations V Bergholm, J Izaac, M Schuld, C Gogolin, C Blank, K McKiernan, ... arXiv preprint arXiv:1811.04968, 2018 | 47 | 2018 |
| Machine learning method for state preparation and gate synthesis on photonic quantum computers JM Arrazola, TR Bromley, J Izaac, CR Myers, K Brádler, N Killoran Quantum Science and Technology 4 (2), 024004, 2019 | 44 | 2019 |
| Generating and designing DNA with deep generative models N Killoran, LJ Lee, A Delong, D Duvenaud, BJ Frey arXiv preprint arXiv:1712.06148, 2017 | 43 | 2017 |
| Derivation and experimental test of fidelity benchmarks for remote preparation of arbitrary qubit states N Killoran, DN Biggerstaff, R Kaltenbaek, KJ Resch, N Lütkenhaus Physical Review A 81 (1), 012334, 2010 | 39 | 2010 |
| Using and reusing coherence to realize quantum processes MG Díaz, K Fang, X Wang, M Rosati, M Skotiniotis, J Calsamiglia, ... Quantum 2, 100, 2018 | 38 | 2018 |
| Quantum natural gradient J Stokes, J Izaac, N Killoran, G Carleo Quantum 4, 269, 2020 | 27 | 2020 |
| Strong quantitative benchmarking of quantum optical devices N Killoran, N Lütkenhaus Physical Review A 83 (5), 052320, 2011 | 22 | 2011 |
| Gaussian boson sampling using threshold detectors N Quesada, JM Arrazola, N Killoran Physical Review A 98 (6), 062322, 2018 | 21 | 2018 |
| Optimal working points for continuous-variable quantum channels I Khan, C Wittmann, N Jain, N Killoran, N Lütkenhaus, C Marquardt, ... Physical Review A 88 (1), 010302, 2013 | 18 | 2013 |
Josh IzaacSchool of Physics, University of Western AustraliaVerified email at uwa.edu.au
