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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
An initialization strategy for addressing barren plateaus in parametrized quantum circuits
E Grant, L Wossnig, M Ostaszewski, M Benedetti
Quantum 3, 214, 2019
1882019
Hierarchical quantum classifiers
E Grant, M Benedetti, S Cao, A Hallam, J Lockhart, V Stojevic, AG Green, ...
npj Quantum Information 4 (1), 1-8, 2018
1452018
Adversarial quantum circuit learning for pure state approximation
M Benedetti, E Grant, L Wossnig, S Severini
New Journal of Physics 21 (4), 043023, 2019
682019
Structure optimization for parameterized quantum circuits
M Ostaszewski, E Grant, M Benedetti
Quantum 5, 391, 2021
652021
Learning hard quantum distributions with variational autoencoders
A Rocchetto, E Grant, S Strelchuk, G Carleo, S Severini
npj Quantum Information 4 (1), 28, 2018
502018
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
502017
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
462018
Quantum circuit structure learning
M Ostaszewski, E Grant, M Benedetti
arXiv preprint arXiv:1905.09692 41, 2019
432019
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
332019
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, ...
arXiv preprint arXiv:2111.05176, 2021
312021
Deep disentangled representations for volumetric reconstruction
E Grant, P Kohli, M Gerven
European Conference on Computer Vision, 266-279, 2016
272016
Hierarchical quantum classifiers, npj Quantum Inf
E Grant, M Benedetti, S Cao, A Hallam, J Lockhart, V Stojevic, AG Green, ...
222018
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
172020
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
152020
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
92021
Compact neural networks based on the multiscale entanglement renormalization ansatz
A Hallam, E Grant, V Stojevic, S Severini, AG Green
BMVC 2018, 2017
92017
Machine learning logical gates for quantum error correction
H Chen, M Vasmer, NP Breuckmann, E Grant
arXiv preprint arXiv:1912.10063, 2019
62019
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
32016
Method for Identifying a Valid Energy State
JLG Tilly, EN Grant
US Patent App. 17/147,879, 2021
2021
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