Patrick J. Coles

Artificial Intelligence · 2013–2022

A researcher in the Science corpus: 14 papers; trusts 81 researchers and is trusted by 16 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 371 citations into it; #8,728 of 35,345 by trust here, #6,468 by citations
• Atomic and Molecular Physics, and Optics — 227 citations into it; #3,126 of 7,135 by trust here, #3,591 by citations
• Computational Theory and Mathematics — 46 citations into it; #12,000 of 12,182 by trust here, #3,448 by citations
• Electrical and Electronic Engineering — 32 citations into it; #15,477 of 16,539 by trust here, #9,902 by citations
• Statistical and Nonlinear Physics — 19 citations into it
• Statistics and Probability — 13 citations into it
• Management Science and Operations Research — 9 citations into it
• Condensed Matter Physics — 5 citations into it

Whom Patrick J. Coles trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Renato Renner
2. Jarrod R. McClean
3. Edward Farhi
4. Maria Schuld
5. M. Cerezo
6. John Preskill
7. Aram Wettroth Harrow
8. Suguru Endo
9. Kristan Temme
10. Marco Tomamichel

Who trusts Patrick J. Coles overall

1. M. Cerezo
2. Martín Larocca
3. Feihu Xu
4. Piotr Czarnik
5. Xiongfeng Ma
6. Samson Wang
7. Eric R. Anschuetz

Papers from Patrick J. Coles's perspective

Ordered by how strongly the researchers Patrick J. Coles trusts endorse each paper. Same corpus, a different order for every researcher.

1. Quantum Computation and Quantum Information
2. A Quantum Approximate Optimization Algorithm
3. Quantum Computation and Quantum Information: Bibliography
4. Quantum Computing in the NISQ era and beyond (Quantum)
5. Quantum Machine Learning in Feature Hilbert Spaces. (Physical Review Letters)
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. Supervised learning with quantum-enhanced feature spaces (Nature)
8. Supervised Learning with Tensor Networks (Neural Information Processing Systems)
9. Multivariate stochastic approximation using a simultaneous perturbation gradient approximation
10. Barren plateaus in quantum neural network training landscapes (Nature Communications)

Their papers

• Variational quantum algorithms (2020) — 3,982 citations
• Error mitigation with Clifford quantum-circuit data (2020) — 310 citations
• Cost function dependent barren plateaus in shallow parametrized quantum circuits (2021) — 1,279 citations
• Self-referenced continuous-variable quantum key distribution protocol (2015) — 178 citations
• Challenges and opportunities in quantum machine learning (2022) — 804 citations
• Generalization in quantum machine learning from few training data (2021) — 559 citations
• Diagnosing Barren Plateaus with Tools from Quantum Optimal Control (2021) — 300 citations
• Connecting ansatz expressibility to gradient magnitudes and barren plateaus (2021) — 650 citations
• Noise-induced barren plateaus in variational quantum algorithms (2020) — 964 citations
• Absence of Barren Plateaus in Quantum Convolutional Neural Networks (2020) — 389 citations
• Variational Quantum Linear Solver (2019) — 377 citations
• Quantum-assisted quantum compiling (2018) — 413 citations
• Entropic uncertainty relations and their applications (2015) — 544 citations
• Improved entropic uncertainty relations and information exclusion relations (2013) — 169 citations