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Edward Grant
Edward Grant
University College London, PhD, Quantum Machine Learning
Verified email at ucl.ac.uk
Title
Cited by
Cited by
Year
The variational quantum eigensolver: a review of methods and best practices
J Tilly, H Chen, S Cao, D Picozzi, K Setia, Y Li, E Grant, L Wossnig, ...
Physics Reports 986, 1-128, 2022
5242022
An initialization strategy for addressing barren plateaus in parametrized quantum circuits
E Grant, L Wossnig, M Ostaszewski, M Benedetti
Quantum 3, 214, 2019
3752019
Hierarchical quantum classifiers
E Grant, M Benedetti, S Cao, A Hallam, J Lockhart, V Stojevic, AG Green, ...
npj Quantum Information 4 (1), 65, 2018
257*2018
Structure optimization for parameterized quantum circuits
M Ostaszewski, E Grant, M Benedetti
Quantum 5, 391, 2021
1802021
Adversarial quantum circuit learning for pure state approximation
M Benedetti, E Grant, L Wossnig, S Severini
New Journal of Physics 21 (4), 043023, 2019
882019
Modelling non-markovian quantum processes with recurrent neural networks
L Banchi, E Grant, A Rocchetto, S Severini
New Journal of Physics 20 (12), 123030, 2018
822018
Learning hard quantum distributions with variational autoencoders
A Rocchetto, E Grant, S Strelchuk, G Carleo, S Severini
npj Quantum Information 4 (1), 28, 2018
712018
Learning hard quantum distributions with variational autoencoders
A Rocchetto, E Grant, S Strelchuk, G Carleo, S Severini
NIPS 2017, Machine Learning for Molecules and Materials, 2017
712017
Dynamical mean field theory algorithm and experiment on quantum computers
I Rungger, N Fitzpatrick, H Chen, CH Alderete, H Apel, A Cowtan, ...
arXiv preprint arXiv:1910.04735, 2019
542019
Quantum circuit structure learning
M Ostaszewski, E Grant, M Benedetti
arXiv preprint arXiv:1905.09692 41, 2019
492019
Reduced density matrix sampling: Self-consistent embedding and multiscale electronic structure on current generation quantum computers
J Tilly, PV Sriluckshmy, A Patel, E Fontana, I Rungger, E Grant, ...
Physical Review Research 3 (3), 033230, 2021
442021
Computation of molecular excited states on IBM quantum computers using a discriminative variational quantum eigensolver
J Tilly, G Jones, H Chen, L Wossnig, E Grant
Physical Review A 102 (6), 062425, 2020
33*2020
Deep disentangled representations for volumetric reconstruction
E Grant, P Kohli, M Van Gerven
Computer Vision–ECCV 2016 Workshops: Amsterdam, The Netherlands, October 8 …, 2016
312016
Cost-function embedding and dataset encoding for machine learning with parametrized quantum circuits
S Cao, L Wossnig, B Vlastakis, P Leek, E Grant
Physical Review A 101 (5), 052309, 2020
282020
Compact neural networks based on the multiscale entanglement renormalization ansatz
A Hallam, E Grant, V Stojevic, S Severini, AG Green
BMVC 2018, 2017
142017
Machine learning logical gates for quantum error correction
H Chen, M Vasmer, NP Breuckmann, E Grant
arXiv preprint arXiv:1912.10063, 2019
82019
Predicting and visualizing psychological attributions with a deep neural network
E Grant, S Sahm, M Zabihi, M van Gerven
2016 23rd International Conference on Pattern Recognition (ICPR), 1-6, 2016
42016
QUANTUM COMPUTING SYSTEM AND METHOD
S Cao, H Chen, E Grant, J Tilly
US Patent App. 18/271,918, 2024
2024
Automated discovery of logical gates for quantum error correction
H Chen, M Vasmer, NP Breuckmann, E Grant
Quantum Information and Computation 22 (11-12), 947-964, 2022
2022
Supplementary
H Chen, M Vasmer, NP Breuckmann, E Grant
Quant. Inf. Comput. 22 (arXiv: 1912.10063), 2022
2022
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