Patrick J. Coles

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 55

Top Topics

Quantum Computing

Machine Learning

Top Venues

Nat. Comput. Sci.

Quantum Mach. Intell.

Publications

Kaelan Donatella, Samuel Duffield, Maxwell Aifer, Denis Melanson, Gavin E. Crooks, Patrick J. Coles
Thermodynamic Natural Gradient Descent. 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)
Maxwell Aifer, Denis Melanson, Kaelan Donatella, Gavin E. Crooks, Thomas Ahle, Patrick J. Coles
Error Mitigation for Thermodynamic Computing. CoRR (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)
Denis Melanson, Mohammad Abu Khater, Maxwell Aifer, Kaelan Donatella, Max Hunter Gordon, Thomas Ahle, Gavin E. Crooks, Antonio J. Martinez, Faris M. Sbahi, Patrick J. Coles
Thermodynamic Computing System for AI Applications. CoRR (2023)
Patrick J. Coles, Collin Szczepanski, Denis Melanson, Kaelan Donatella, Antonio J. Martinez, Faris M. Sbahi
Thermodynamic AI and the Fluctuation Frontier. ICRC (2023)
Maxwell Aifer, Kaelan Donatella, Max Hunter Gordon, Thomas Ahle, Daniel Simpson, Gavin E. Crooks, Patrick J. Coles
Thermodynamic Linear Algebra. CoRR (2023)
Samuel Duffield, Maxwell Aifer, Gavin E. Crooks, Thomas Ahle, Patrick J. Coles
Thermodynamic Matrix Exponentials and Thermodynamic Parallelism. CoRR (2023)
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)
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)
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)
Sofiène Jerbi, Joe Gibbs, Manuel S. Rudolph, Matthias C. Caro, Patrick J. Coles, Hsin-Yuan Huang, Zoë Holmes
The power and limitations of learning quantum dynamics incoherently. CoRR (2023)
Patrick J. Coles
Thermodynamic AI and the fluctuation frontier. CoRR (2023)
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)
Andi Gu, Lukasz Cincio, Patrick J. Coles
Practical Black Box Hamiltonian Learning. 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)
Matthias C. Caro, Hsin-Yuan Huang, Nicholas Ezzell, Joe Gibbs, Andrew T. Sornborger, Lukasz Cincio, Patrick J. Coles, Zoë Holmes
Out-of-distribution generalization for learning quantum dynamics. CoRR (2022)
Nic Ezzell, Zoë Holmes, Patrick J. Coles
The quantum low-rank approximation problem. CoRR (2022)
Joe Gibbs, Zoë Holmes, Matthias C. Caro, Nicholas Ezzell, Hsin-Yuan Huang, Lukasz Cincio, Andrew T. Sornborger, Patrick J. Coles
Dynamical simulation via quantum machine learning with provable generalization. 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)
Piotr Czarnik, Andrew Arrasmith, Patrick J. Coles, Lukasz Cincio
Error mitigation with Clifford quantum-circuit data. Quantum 5 (2021)
Louis Schatzki, Andrew Arrasmith, Patrick J. Coles, M. Cerezo
Entangled Datasets for Quantum Machine Learning. CoRR (2021)
Matthias C. Caro, Hsin-Yuan Huang, M. Cerezo, Kunal Sharma, Andrew T. Sornborger, Lukasz Cincio, Patrick J. Coles
Generalization in quantum machine learning from few training data. CoRR (2021)
Joe Gibbs, Kaitlin Gili, Zoë Holmes, Benjamin Commeau, Andrew Arrasmith, Lukasz Cincio, Patrick J. Coles, Andrew T. Sornborger
Long-time simulations with high fidelity on quantum hardware. CoRR (2021)
Andrew Arrasmith, Zoë Holmes, M. Cerezo, Patrick J. Coles
Equivalence of quantum barren plateaus to cost concentration and narrow gorges. CoRR (2021)
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)
Andi Gu, Angus Lowe, Pavel A. Dub, Patrick J. Coles, Andrew Arrasmith
Adaptive shot allocation for fast convergence in variational quantum algorithms. CoRR (2021)
Samson Wang, Piotr Czarnik, Andrew Arrasmith, M. Cerezo, Lukasz Cincio, Patrick J. Coles
Can Error Mitigation Improve Trainability of Noisy Variational Quantum Algorithms? CoRR (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)
Patrick J. Coles
Seeking quantum advantage for neural networks. Nat. Comput. Sci. 1 (6) (2021)
Martin Larocca, Nathan Ju, Diego García-Martín, Patrick J. Coles, M. Cerezo
Theory of overparametrization in quantum neural networks. CoRR (2021)
Zoë Holmes, Kunal Sharma, M. Cerezo, Patrick J. Coles
Connecting ansatz expressibility to gradient magnitudes and barren plateaus. CoRR (2021)
Dhrumil Patel, Patrick J. Coles, Mark M. Wilde
Variational Quantum Algorithms for Semidefinite Programming. CoRR (2021)
Jonas M. Kübler, Andrew Arrasmith, Lukasz Cincio, Patrick J. Coles
An Adaptive Optimizer for Measurement-Frugal Variational Algorithms. Quantum 4 (2020)
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)
Arthur Pesah, M. Cerezo, Samson Wang, Tyler Volkoff, Andrew T. Sornborger, Patrick J. Coles
Absence of Barren Plateaus in Quantum Convolutional Neural Networks. 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)
Enrico Fontana, M. Cerezo, Andrew Arrasmith, Ivan Rungger, Patrick J. Coles
Optimizing parametrized quantum circuits via noise-induced breaking of symmetries. 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)
Patrick J. Coles, Stephan J. Eidenbenz, Scott Pakin, Adetokunbo Adedoyin, John Ambrosiano, Petr M. Anisimov, William Casper, Gopinath Chennupati, Carleton Coffrin, Hristo N. Djidjev, David Gunter, Satish Karra, Nathan Lemons, Shizeng Lin, Andrey Y. Lokhov, Alexander Malyzhenkov, David Dennis Lee Mascarenas, Susan M. Mniszewski, Balu Nadiga, Dan O'Malley, Diane Oyen, Lakshman Prasad, Randy Roberts, Philip Romero, Nandakishore Santhi, Nikolai Sinitsyn, Pieter Swart, Marc Vuffray, Jim Wendelberger, Boram Yoon, Richard J. Zamora, Wei Zhu
Quantum Algorithm Implementations for Beginners. CoRR (2018)