Marco Cerezo - RankMe

52 papers Journal 52

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Quantum Circuit Pre-Synthesis: Learning Local Edits to Reduce T-count. CoRR Daniele Lizzio Bosco, Lukasz Cincio, Giuseppe Serra, Marco Cerezo
2024	J	`jnl`	A Review of Barren Plateaus in Variational Quantum Computing. CoRR Martin Larocca, Supanut Thanasilp, Samson Wang, Kunal Sharma, Jacob D. Biamonte, Patrick J. Coles, Lukasz Cincio, Jarrod R. McClean, Zoë Holmes, Marco Cerezo
2024	J	`jnl`	Architectures and random properties of symplectic quantum circuits. CoRR Diego García-Martín, Paolo Braccia, Marco Cerezo
2024	J	`jnl`	Can Error Mitigation Improve Trainability of Noisy Variational Quantum Algorithms? Quantum Samson Wang, Piotr Czarnik, Andrew Arrasmith, Marco Cerezo, Lukasz Cincio, Patrick J. Coles
2024	J	`jnl`	Classically estimating observables of noiseless quantum circuits. CoRR Armando Angrisani, Alexander Schmidhuber, Manuel S. Rudolph, Marco Cerezo, Zoë Holmes, Hsin-Yuan Huang
2024	J	`jnl`	Computing exact moments of local random quantum circuits via tensor networks. Quantum Mach. Intell. Paolo Braccia, Pablo Bermejo, Lukasz Cincio, Marco Cerezo
2024	J	`jnl`	Efficient quantum-enhanced classical simulation for patches of quantum landscapes. CoRR Sacha Lerch, Ricard Puig-i-Valls, Manuel S. Rudolph, Armando Angrisani, Tyson Jones, Marco Cerezo, Supanut Thanasilp, Zoë Holmes
2024	J	`jnl`	Exact spectral gaps of random one-dimensional quantum circuits. CoRR Andrew E. Deneris, Pablo Bermejo, Paolo Braccia, Lukasz Cincio, Marco Cerezo
2024	J	`jnl`	Gate-based quantum simulation of Gaussian bosonic circuits on exponentially many modes. CoRR Alice Barthe, Marco Cerezo, Andrew T. Sornborger, Martin Larocca, Diego García-Martín
2024	J	`jnl`	On the practical usefulness of the Hardware Efficient Ansatz. Quantum Lorenzo Leone, Salvatore F. E. Oliviero, Lukasz Cincio, Marco Cerezo
2024	J	`jnl`	Quantum Convolutional Neural Networks are (Effectively) Classically Simulable. CoRR Pablo Bermejo, Paolo Braccia, Manuel S. Rudolph, Zoë Holmes, Lukasz Cincio, Marco Cerezo
2024	J	`jnl`	Random ensembles of symplectic and unitary states are indistinguishable. CoRR Maxwell West, Antonio Anna Mele, Martin Larocca, Marco Cerezo
2023	J	`jnl`	A semi-agnostic ansatz with variable structure for variational quantum algorithms. Quantum Mach. Intell. Matías Bilkis, Marco Cerezo, Guillaume Verdon, Patrick J. Coles, Lukasz Cincio
2023	J	`jnl`	Challenges and Opportunities in Quantum Machine Learning. CoRR Marco Cerezo, Guillaume Verdon, Hsin-Yuan Huang, Lukasz Cincio, Patrick J. Coles
2023	J	`jnl`	Deep quantum neural networks form Gaussian processes. CoRR Diego García-Martín, Martin Larocca, Marco Cerezo
2023	J	`jnl`	Does provable absence of barren plateaus imply classical simulability? Or, why we need to rethink variational quantum computing. CoRR Marco Cerezo, Martin Larocca, Diego García-Martín, Nelson L. Diaz, Paolo Braccia, Enrico Fontana, Manuel S. Rudolph, Pablo Bermejo, Aroosa Ijaz, Supanut Thanasilp, Eric R. Anschuetz, Zoë Holmes
2023	J	`jnl`	Effects of noise on the overparametrization of quantum neural networks. CoRR Diego García-Martín, Martin Larocca, Marco Cerezo
2023	J	`jnl`	On the universality of S CoRR Sujay Kazi, Martin Larocca, Marco Cerezo
2023	J	`jnl`	Subtleties in the trainability of quantum machine learning models. Quantum Mach. Intell. Supanut Thanasilp, Samson Wang, Nhat A. Nghiem, Patrick J. Coles, Marco Cerezo
2023	J	`jnl`	The battle of clean and dirty qubits in the era of partial error correction. Quantum Daniel Bultrini, Samson Wang, Piotr Czarnik, Max Hunter Gordon, Marco Cerezo, Patrick J. Coles, Lukasz Cincio
2023	J	`jnl`	Theory of overparametrization in quantum neural networks. Nat. Comput. Sci. Martin Larocca, Nathan Ju, Diego García-Martín, Patrick J. Coles, Marco Cerezo
2023	J	`jnl`	Unifying and benchmarking state-of-the-art quantum error mitigation techniques. Quantum Daniel Bultrini, Max Hunter Gordon, Piotr Czarnik, Andrew Arrasmith, Marco Cerezo, Patrick J. Coles, Lukasz Cincio
2023	J	`jnl`	Variational Quantum Linear Solver. Quantum Carlos Bravo-Prieto, Ryan LaRose, Marco Cerezo, Yigit Subasi, Lukasz Cincio, Patrick J. Coles
2022	J	`jnl`	Challenges and opportunities in quantum machine learning. Nat. Comput. Sci. Marco Cerezo, Guillaume Verdon, Hsin-Yuan Huang, Lukasz Cincio, Patrick J. Coles
2022	J	`jnl`	Covariance matrix preparation for quantum principal component analysis. CoRR Max Hunter Gordon, Marco Cerezo, Lukasz Cincio, Patrick J. Coles
2022	J	`jnl`	Diagnosing Barren Plateaus with Tools from Quantum Optimal Control. Quantum Martin Larocca, Piotr Czarnik, Kunal Sharma, Gopikrishnan Muraleedharan, Patrick J. Coles, Marco Cerezo
2022	J	`jnl`	Exponential concentration and untrainability in quantum kernel methods. CoRR Supanut Thanasilp, Samson Wang, Marco Cerezo, Zoë Holmes
2022	J	`jnl`	Group-Invariant Quantum Machine Learning. CoRR Martin Larocca, Frederic Sauvage, Faris M. Sbahi, Guillaume Verdon, Patrick J. Coles, Marco Cerezo
2022	J	`jnl`	Inference-Based Quantum Sensing. CoRR Cinthia Huerta Alderete, Max Hunter Gordon, Frederic Sauvage, Akira Sone, Andrew T. Sornborger, Patrick J. Coles, Marco Cerezo
2022	J	`jnl`	Non-trivial symmetries in quantum landscapes and their resilience to quantum noise. Quantum Enrico Fontana, Marco Cerezo, Andrew Arrasmith, Ivan Rungger, Patrick J. Coles
2022	J	`jnl`	Representation Theory for Geometric Quantum Machine Learning. CoRR Michael Ragone, Paolo Braccia, Quynh T. Nguyen, Louis Schatzki, Patrick J. Coles, Frederic Sauvage, Martin Larocca, Marco Cerezo
2022	J	`jnl`	Resource frugal optimizer for quantum machine learning. CoRR Charles Moussa, Max Hunter Gordon, Michal Baczyk, Marco Cerezo, Lukasz Cincio, Patrick J. Coles
2022	J	`jnl`	Theoretical Guarantees for Permutation-Equivariant Quantum Neural Networks. CoRR Louis Schatzki, Martin Larocca, Frederic Sauvage, Marco Cerezo
2022	J	`jnl`	Theory for Equivariant Quantum Neural Networks. CoRR Quynh T. Nguyen, Louis Schatzki, Paolo Braccia, Michael Ragone, Patrick J. Coles, Frederic Sauvage, Martin Larocca, Marco Cerezo
2021	J	`jnl`	A semi-agnostic ansatz with variable structure for quantum machine learning. CoRR Matías Bilkis, Marco Cerezo, Guillaume Verdon, Patrick J. Coles, Lukasz Cincio
2021	J	`jnl`	Can Error Mitigation Improve Trainability of Noisy Variational Quantum Algorithms? CoRR Samson Wang, Piotr Czarnik, Andrew Arrasmith, Marco Cerezo, Lukasz Cincio, Patrick J. Coles
2021	J	`jnl`	Connecting ansatz expressibility to gradient magnitudes and barren plateaus. CoRR Zoë Holmes, Kunal Sharma, Marco Cerezo, Patrick J. Coles
2021	J	`jnl`	Effect of barren plateaus on gradient-free optimization. Quantum Andrew Arrasmith, Marco Cerezo, Piotr Czarnik, Lukasz Cincio, Patrick J. Coles
2021	J	`jnl`	Entangled Datasets for Quantum Machine Learning. CoRR Louis Schatzki, Andrew Arrasmith, Patrick J. Coles, Marco Cerezo
2021	J	`jnl`	Equivalence of quantum barren plateaus to cost concentration and narrow gorges. CoRR Andrew Arrasmith, Zoë Holmes, Marco Cerezo, Patrick J. Coles
2021	J	`jnl`	Generalization in quantum machine learning from few training data. CoRR Matthias C. Caro, Hsin-Yuan Huang, Marco Cerezo, Kunal Sharma, Andrew T. Sornborger, Lukasz Cincio, Patrick J. Coles
2021	J	`jnl`	Subtleties in the trainability of quantum machine learning models. CoRR Supanut Thanasilp, Samson Wang, Nhat A. Nghiem, Patrick J. Coles, Marco Cerezo
2021	J	`jnl`	Theory of overparametrization in quantum neural networks. CoRR Martin Larocca, Nathan Ju, Diego García-Martín, Patrick J. Coles, Marco Cerezo
2020	J	`jnl`	Absence of Barren Plateaus in Quantum Convolutional Neural Networks. CoRR Arthur Pesah, Marco Cerezo, Samson Wang, Tyler J. Volkoff, Andrew T. Sornborger, Patrick J. Coles
2020	J	`jnl`	Cost-Function-Dependent Barren Plateaus in Shallow Quantum Neural Networks. CoRR Marco Cerezo, Akira Sone, Tyler J. Volkoff, Lukasz Cincio, Patrick J. Coles
2020	J	`jnl`	Effect of barren plateaus on gradient-free optimization. CoRR Andrew Arrasmith, Marco Cerezo, Piotr Czarnik, Lukasz Cincio, Patrick J. Coles
2020	J	`jnl`	Noise-Induced Barren Plateaus in Variational Quantum Algorithms. CoRR Samson Wang, Enrico Fontana, Marco Cerezo, Kunal Sharma, Akira Sone, Lukasz Cincio, Patrick J. Coles
2020	J	`jnl`	Optimizing parametrized quantum circuits via noise-induced breaking of symmetries. CoRR Enrico Fontana, Marco Cerezo, Andrew Arrasmith, Ivan Rungger, Patrick J. Coles
2020	J	`jnl`	Reformulation of the No-Free-Lunch Theorem for Entangled Data Sets. CoRR Kunal Sharma, Marco Cerezo, Zoë Holmes, Lukasz Cincio, Andrew T. Sornborger, Patrick J. Coles
2020	J	`jnl`	Trainability of Dissipative Perceptron-Based Quantum Neural Networks. CoRR Kunal Sharma, Marco Cerezo, Lukasz Cincio, Patrick J. Coles
2020	J	`jnl`	Variational Quantum Algorithms. CoRR Marco Cerezo, Andrew Arrasmith, Ryan Babbush, Simon C. Benjamin, Suguru Endo, Keisuke Fujii, Jarrod R. McClean, Kosuke Mitarai, Xiao Yuan, Lukasz Cincio, Patrick J. Coles
2020	J	`jnl`	Variational Quantum Fidelity Estimation. Quantum Marco Cerezo, Alexander Poremba, Lukasz Cincio, Patrick J. Coles