Leonard Wossnig
Title
Cited by
Cited by
Year
Quantum machine learning: a classical perspective
C Ciliberto, M Herbster, AD Ialongo, M Pontil, A Rocchetto, S Severini, ...
Proceedings of the Royal Society A: Mathematical, Physical and Engineering …, 2018
1002018
Quantum linear system algorithm for dense matrices
L Wossnig, Z Zhao, A Prakash
Physical review letters 120 (5), 050502, 2018
782018
Quantum gradient descent and Newton's method for constrained polynomial optimization
P Rebentrost, M Schuld, L Wossnig, F Petruccione, S Lloyd
https://arxiv.org/abs/1612.01789, 2017
552017
An initialization strategy for addressing barren plateaus in parametrized quantum circuits
E Grant, L Wossnig, M Ostaszewski, M Benedetti
Quantum 3, 214, 2019
262019
Adversarial quantum circuit learning for pure state approximation
M Benedetti, E Grant, L Wossnig, S Severini
New Journal of Physics 21 (4), 043023, 2019
232019
Quantum linear systems algorithms: a primer
D Dervovic, M Herbster, P Mountney, S Severini, N Usher, L Wossnig
arXiv preprint arXiv:1802.08227, 2018
182018
Universal discriminative quantum neural networks
H Chen, L Wossnig, S Severini, H Neven, M Mohseni
arXiv preprint arXiv:1805.08654, 2018
162018
A quantum algorithm for simulating non-sparse Hamiltonians
C Wang, L Wossnig
arXiv preprint arXiv:1803.08273, 2018
122018
Generative training of quantum Boltzmann machines with hidden units
N Wiebe, L Wossnig
arXiv preprint arXiv:1905.09902, 2019
82019
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
62019
Approximating Hamiltonian dynamics with the Nyström method
A Rudi, L Wossnig, C Ciliberto, A Rocchetto, M Pontil, S Severini
Quantum 4, 234, 2020
42020
The Role of Information in Group Formation.
S Bennati, L Wossnig, J Thiele
ICAART (1), 231-235, 2016
32016
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
22020
Fast quantum learning with statistical guarantees
C Ciliberto, A Rocchetto, A Rudi, L Wossnig
arXiv preprint arXiv:2001.10477, 2020
12020
Computation of molecular excited states on IBMQ using a Discriminative Variational Quantum Eigensolver
J Tilly, G Jones, H Chen, L Wossnig, E Grant
arXiv preprint arXiv:2001.04941, 2020
12020
Quantum machine learning: Challenges and Opportunities
L Wossnig, S Severini
APS 2019, K27. 007, 2019
12019
Quantum-classical truncated Newton method for high-dimensional energy landscapes
L Wossnig, S Tschiatschek, S Zohren
arXiv preprint arXiv:1710.07063, 2017
12017
Quantum State Discrimination Using Noisy Quantum Neural Networks
A Patterson, H Chen, L Wossnig, S Severini, D Browne, I Rungger
arXiv preprint arXiv:1911.00352, 2019
2019
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