Marco Cerezo

Publication Activity (10 Years)

Years Active: 2020-2024
Publications (10 Years): 36

Top Topics

Gaussian Process

Steepest Descent Method

Machine Learning

Top Venues

Quantum Mach. Intell.

Nat. Comput. Sci.

Publications

Alice Barthe, Marco Cerezo, Andrew T. Sornborger, Martin Larocca, Diego García-Martín
Gate-based quantum simulation of Gaussian bosonic circuits on exponentially many modes. CoRR (2024)
Diego García-Martín, Paolo Braccia, Marco Cerezo
Architectures and random properties of symplectic quantum circuits. CoRR (2024)
Samson Wang, Piotr Czarnik, Andrew Arrasmith, Marco Cerezo, Lukasz Cincio, Patrick J. Coles
Can Error Mitigation Improve Trainability of Noisy Variational Quantum Algorithms? Quantum 8 (2024)
Martin Larocca, Supanut Thanasilp, Samson Wang, Kunal Sharma, Jacob D. Biamonte, Patrick J. Coles, Lukasz Cincio, Jarrod R. McClean, Zoë Holmes, Marco Cerezo
A Review of Barren Plateaus in Variational Quantum Computing. CoRR (2024)
Daniel Bultrini, Samson Wang, Piotr Czarnik, Max Hunter Gordon, Marco Cerezo, Patrick J. Coles, Lukasz Cincio
The battle of clean and dirty qubits in the era of partial error correction. Quantum 7 (2023)
Diego García-Martín, Martin Larocca, Marco Cerezo
Deep quantum neural networks form Gaussian processes. CoRR (2023)
Marco Cerezo, Guillaume Verdon, Hsin-Yuan Huang, Lukasz Cincio, Patrick J. Coles
Challenges and Opportunities in Quantum Machine Learning. CoRR (2023)
Carlos Bravo-Prieto, Ryan Larose, Marco Cerezo, Yigit Subasi, Lukasz Cincio, Patrick J. Coles
Variational Quantum Linear Solver. Quantum 7 (2023)
Diego García-Martín, Martin Larocca, Marco Cerezo
Effects of noise on the overparametrization of quantum neural networks. CoRR (2023)
Sujay Kazi, Martin Larocca, Marco Cerezo
-equivariant k-body gates. CoRR (2023)
Supanut Thanasilp, Samson Wang, Nhat A. Nghiem, Patrick J. Coles, Marco Cerezo
Subtleties in the trainability of quantum machine learning models. Quantum Mach. Intell. 5 (1) (2023)
M. Bilkis, Marco Cerezo, Guillaume Verdon, Patrick J. Coles, Lukasz Cincio
A semi-agnostic ansatz with variable structure for variational quantum algorithms. Quantum Mach. Intell. 5 (2) (2023)
Daniel Bultrini, Max Hunter Gordon, Piotr Czarnik, Andrew Arrasmith, Marco Cerezo, Patrick J. Coles, Lukasz Cincio
Unifying and benchmarking state-of-the-art quantum error mitigation techniques. Quantum 7 (2023)
Martin Larocca, Nathan Ju, Diego García-Martín, Patrick J. Coles, Marco Cerezo
Theory of overparametrization in quantum neural networks. Nat. Comput. Sci. 3 (6) (2023)
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
Does provable absence of barren plateaus imply classical simulability? Or, why we need to rethink variational quantum computing. CoRR (2023)
Supanut Thanasilp, Samson Wang, Marco Cerezo, Zoë Holmes
Exponential concentration and untrainability in quantum kernel methods. CoRR (2022)
Martin Larocca, Frederic Sauvage, Faris M. Sbahi, Guillaume Verdon, Patrick J. Coles, Marco Cerezo
Group-Invariant Quantum Machine Learning. CoRR (2022)
Martin Larocca, Piotr Czarnik, Kunal Sharma, Gopikrishnan Muraleedharan, Patrick J. Coles, Marco Cerezo
Diagnosing Barren Plateaus with Tools from Quantum Optimal Control. Quantum 6 (2022)
Louis Schatzki, Martin Larocca, Frederic Sauvage, Marco Cerezo
Theoretical Guarantees for Permutation-Equivariant Quantum Neural Networks. CoRR (2022)
Charles Moussa, Max Hunter Gordon, Michal Baczyk, Marco Cerezo, Lukasz Cincio, Patrick J. Coles
Resource frugal optimizer for quantum machine learning. CoRR (2022)
Quynh T. Nguyen, Louis Schatzki, Paolo Braccia, Michael Ragone, Patrick J. Coles, Frederic Sauvage, Martin Larocca, Marco Cerezo
Theory for Equivariant Quantum Neural Networks. CoRR (2022)
Marco Cerezo, Guillaume Verdon, Hsin-Yuan Huang, Lukasz Cincio, Patrick J. Coles
Challenges and opportunities in quantum machine learning. Nat. Comput. Sci. 2 (9) (2022)
Max Hunter Gordon, Marco Cerezo, Lukasz Cincio, Patrick J. Coles
Covariance matrix preparation for quantum principal component analysis. CoRR (2022)
Michael Ragone, Paolo Braccia, Quynh T. Nguyen, Louis Schatzki, Patrick J. Coles, Frederic Sauvage, Martin Larocca, Marco Cerezo
Representation Theory for Geometric Quantum Machine Learning. CoRR (2022)
Cinthia Huerta Alderete, Max Hunter Gordon, Frederic Sauvage, Akira Sone, Andrew T. Sornborger, Patrick J. Coles, Marco Cerezo
Inference-Based Quantum Sensing. CoRR (2022)
Enrico Fontana, Marco Cerezo, Andrew Arrasmith, Ivan Rungger, Patrick J. Coles
Non-trivial symmetries in quantum landscapes and their resilience to quantum noise. Quantum 6 (2022)
Supanut Thanasilp, Samson Wang, Nhat A. Nghiem, Patrick J. Coles, Marco Cerezo
Subtleties in the trainability of quantum machine learning models. CoRR (2021)
Andrew Arrasmith, Marco Cerezo, Piotr Czarnik, Lukasz Cincio, Patrick J. Coles
Effect of barren plateaus on gradient-free optimization. Quantum 5 (2021)
M. Bilkis, Marco Cerezo, Guillaume Verdon, Patrick J. Coles, Lukasz Cincio
A semi-agnostic ansatz with variable structure for quantum machine learning. CoRR (2021)
Samson Wang, Enrico Fontana, Marco Cerezo, Kunal Sharma, Akira Sone, Lukasz Cincio, Patrick J. Coles
Noise-Induced Barren Plateaus in Variational Quantum Algorithms. CoRR (2020)
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
Variational Quantum Algorithms. CoRR (2020)
Marco Cerezo, Alexander Poremba, Lukasz Cincio, Patrick J. Coles
Variational Quantum Fidelity Estimation. Quantum 4 (2020)
Kunal Sharma, Marco Cerezo, Zoë Holmes, Lukasz Cincio, Andrew T. Sornborger, Patrick J. Coles
Reformulation of the No-Free-Lunch Theorem for Entangled Data Sets. CoRR (2020)
Marco Cerezo, Akira Sone, Tyler Volkoff, Lukasz Cincio, Patrick J. Coles
Cost-Function-Dependent Barren Plateaus in Shallow Quantum Neural Networks. CoRR (2020)
Andrew Arrasmith, Marco Cerezo, Piotr Czarnik, Lukasz Cincio, Patrick J. Coles
Effect of barren plateaus on gradient-free optimization. CoRR (2020)
Kunal Sharma, Marco Cerezo, Lukasz Cincio, Patrick J. Coles
Trainability of Dissipative Perceptron-Based Quantum Neural Networks. CoRR (2020)