Articles with public access mandates - Marco CerezoLearn more
Available somewhere: 39
Variational quantum algorithms
M Cerezo, A Arrasmith, R Babbush, SC Benjamin, S Endo, K Fujii, ...
Nature Reviews Physics 3, 625–644, 2021
Mandates: US Department of Energy, UK Engineering and Physical Sciences Research …
Cost function dependent barren plateaus in shallow parametrized quantum circuits
M Cerezo, A Sone, T Volkoff, L Cincio, PJ Coles
Nature communications 12 (1), 1791, 2021
Mandates: US Department of Energy
Noise-induced barren plateaus in variational quantum algorithms
S Wang, E Fontana, M Cerezo, K Sharma, A Sone, L Cincio, PJ Coles
Nature communications 12 (1), 6961, 2021
Mandates: US Department of Energy, UK Engineering and Physical Sciences Research Council
Connecting ansatz expressibility to gradient magnitudes and barren plateaus
Z Holmes, K Sharma, M Cerezo, PJ Coles
PRX Quantum 3 (1), 010313, 2022
Mandates: US Department of Energy
Variational quantum linear solver
C Bravo-Prieto, R LaRose, M Cerezo, Y Subasi, L Cincio, PJ Coles
Quantum 7, 1188, 2023
Mandates: US Department of Energy
Challenges and opportunities in quantum machine learning
M Cerezo, G Verdon, HY Huang, L Cincio, PJ Coles
Nature Computational Science 2 (9), 567-576, 2022
Mandates: US Department of Energy
Generalization in quantum machine learning from few training data
MC Caro, HY Huang, M Cerezo, K Sharma, A Sornborger, L Cincio, ...
Nature communications 13 (1), 4919, 2022
Mandates: US Department of Energy, US Department of Defense
Absence of barren plateaus in quantum convolutional neural networks
A Pesah, M Cerezo, S Wang, T Volkoff, AT Sornborger, PJ Coles
Physical Review X 11 (4), 041011, 2021
Mandates: US Department of Energy
Effect of barren plateaus on gradient-free optimization
A Arrasmith, M Cerezo, P Czarnik, L Cincio, PJ Coles
Quantum 5, 558, 2021
Mandates: US Department of Energy
Noise resilience of variational quantum compiling
K Sharma, S Khatri, M Cerezo, PJ Coles
New Journal of Physics 22 (4), 043006, 2020
Mandates: US National Science Foundation, US Department of Energy, Natural Sciences …
Diagnosing barren plateaus with tools from quantum optimal control
M Larocca, P Czarnik, K Sharma, G Muraleedharan, PJ Coles, M Cerezo
Quantum 6, 824, 2022
Mandates: US National Science Foundation, US Department of Energy, Government of Argentina
Trainability of dissipative perceptron-based quantum neural networks
K Sharma, M Cerezo, L Cincio, PJ Coles
Physical Review Letters 128 (18), 180505, 2022
Mandates: US Department of Energy
Theory of overparametrization in quantum neural networks
M Larocca, N Ju, D García-Martín, PJ Coles, M Cerezo
Nature Computational Science 3 (6), 542-551, 2023
Mandates: US Department of Energy, European Commission, Government of Spain
Higher order derivatives of quantum neural networks with barren plateaus
M Cerezo, PJ Coles
Quantum Science and Technology 6 (2), 035006, 2021
Mandates: US Department of Energy
Equivalence of quantum barren plateaus to cost concentration and narrow gorges
A Arrasmith, Z Holmes, M Cerezo, PJ Coles
Quantum Science and Technology 7 (4), 045015, 2022
Mandates: US Department of Energy
Group-invariant quantum machine learning
M Larocca, F Sauvage, FM Sbahi, G Verdon, PJ Coles, M Cerezo
PRX Quantum 3 (3), 030341, 2022
Mandates: US Department of Energy
Variational quantum fidelity estimation
M Cerezo, A Poremba, L Cincio, PJ Coles
Quantum 4, 248, 2020
Mandates: US National Science Foundation, US Department of Energy, US Department of …
Variational quantum state eigensolver
M Cerezo, K Sharma, A Arrasmith, PJ Coles
npj Quantum Information 8 (1), 113, 2022
Mandates: US Department of Energy
Variational quantum algorithm for estimating the quantum fisher information
JL Beckey, M Cerezo, A Sone, PJ Coles
Physical Review Research 4 (1), 013083, 2022
Mandates: US National Science Foundation, US Department of Energy
Subtleties in the trainability of quantum machine learning models
S Thanasilp, S Wang, NA Nghiem, P Coles, M Cerezo
Quantum Machine Intelligence 5 (1), 21, 2023
Mandates: US Department of Energy, UK Engineering and Physical Sciences Research …
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