Patrick J. Coles

Orcid: 0000-0001-9879-8425

According to our database1, Patrick J. Coles authored at least 51 papers between 2018 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Links

On csauthors.net:

Bibliography

2024
Can Error Mitigation Improve Trainability of Noisy Variational Quantum Algorithms?
Quantum, March, 2024

Thermodynamic Bayesian Inference.
CoRR, 2024

Thermodynamic Natural Gradient Descent.
CoRR, 2024

A Review of Barren Plateaus in Variational Quantum Computing.
CoRR, 2024

Error Mitigation for Thermodynamic Computing.
CoRR, 2024

2023
A semi-agnostic ansatz with variable structure for variational quantum algorithms.
Quantum Mach. Intell., December, 2023

Variational Quantum Linear Solver.
Quantum, November, 2023

The battle of clean and dirty qubits in the era of partial error correction.
Quantum, July, 2023

Unifying and benchmarking state-of-the-art quantum error mitigation techniques.
Quantum, June, 2023

Subtleties in the trainability of quantum machine learning models.
Quantum Mach. Intell., June, 2023

Theory of overparametrization in quantum neural networks.
Nat. Comput. Sci., 2023

Thermodynamic Computing System for AI Applications.
CoRR, 2023

Thermodynamic Matrix Exponentials and Thermodynamic Parallelism.
CoRR, 2023

Thermodynamic Linear Algebra.
CoRR, 2023

The power and limitations of learning quantum dynamics incoherently.
CoRR, 2023

Thermodynamic AI and the fluctuation frontier.
CoRR, 2023

Thermodynamic AI and the Fluctuation Frontier.
Proceedings of the IEEE International Conference on Rebooting Computing, 2023

2022
Diagnosing Barren Plateaus with Tools from Quantum Optimal Control.
Quantum, September, 2022

Non-trivial symmetries in quantum landscapes and their resilience to quantum noise.
Quantum, September, 2022

Challenges and opportunities in quantum machine learning.
Nat. Comput. Sci., 2022

Resource frugal optimizer for quantum machine learning.
CoRR, 2022

Theory for Equivariant Quantum Neural Networks.
CoRR, 2022

Representation Theory for Geometric Quantum Machine Learning.
CoRR, 2022

Practical Black Box Hamiltonian Learning.
CoRR, 2022

Inference-Based Quantum Sensing.
CoRR, 2022

Group-Invariant Quantum Machine Learning.
CoRR, 2022

Dynamical simulation via quantum machine learning with provable generalization.
CoRR, 2022

Out-of-distribution generalization for learning quantum dynamics.
CoRR, 2022

Covariance matrix preparation for quantum principal component analysis.
CoRR, 2022

The quantum low-rank approximation problem.
CoRR, 2022

2021
Error mitigation with Clifford quantum-circuit data.
Quantum, 2021

Effect of barren plateaus on gradient-free optimization.
Quantum, 2021

Seeking quantum advantage for neural networks.
Nat. Comput. Sci., 2021

Variational Quantum Algorithms for Semidefinite Programming.
CoRR, 2021

Generalization in quantum machine learning from few training data.
CoRR, 2021

Entangled Datasets for Quantum Machine Learning.
CoRR, 2021

Adaptive shot allocation for fast convergence in variational quantum algorithms.
CoRR, 2021

Equivalence of quantum barren plateaus to cost concentration and narrow gorges.
CoRR, 2021

A semi-agnostic ansatz with variable structure for quantum machine learning.
CoRR, 2021

Long-time simulations with high fidelity on quantum hardware.
CoRR, 2021

Connecting ansatz expressibility to gradient magnitudes and barren plateaus.
CoRR, 2021

2020
An Adaptive Optimizer for Measurement-Frugal Variational Algorithms.
Quantum, 2020

Variational Quantum Fidelity Estimation.
Quantum, 2020

Variational Quantum Algorithms.
CoRR, 2020

Optimizing parametrized quantum circuits via noise-induced breaking of symmetries.
CoRR, 2020

Absence of Barren Plateaus in Quantum Convolutional Neural Networks.
CoRR, 2020

Noise-Induced Barren Plateaus in Variational Quantum Algorithms.
CoRR, 2020

Reformulation of the No-Free-Lunch Theorem for Entangled Data Sets.
CoRR, 2020

Trainability of Dissipative Perceptron-Based Quantum Neural Networks.
CoRR, 2020

Cost-Function-Dependent Barren Plateaus in Shallow Quantum Neural Networks.
CoRR, 2020

2018
Quantum Algorithm Implementations for Beginners.
CoRR, 2018


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