Lukasz Cincio

According to our database, Lukasz Cincio authored at least 22 papers between 2019 and 2022.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2022

Resource frugal optimizer for quantum machine learning.

Charles Moussa, Max Hunter Gordon, Michal Baczyk, Marco Cerezo, Lukasz Cincio, Patrick J. Coles

CoRR, 2022

Practical Black Box Hamiltonian Learning.

Andi Gu, Lukasz Cincio, Patrick J. Coles

CoRR, 2022

Dynamical simulation via quantum machine learning with provable generalization.

Joe Gibbs, Zoë Holmes, Matthias C. Caro, Nicholas Ezzell, Hsin-Yuan Huang, Lukasz Cincio, Andrew T. Sornborger, Patrick J. Coles

CoRR, 2022

Out-of-distribution generalization for learning quantum dynamics.

Matthias C. Caro, Hsin-Yuan Huang, Nicholas Ezzell, Joe Gibbs, Andrew T. Sornborger, Lukasz Cincio, Patrick J. Coles, Zoë Holmes

CoRR, 2022

Covariance matrix preparation for quantum principal component analysis.

Max Hunter Gordon, Marco Cerezo, Lukasz Cincio, Patrick J. Coles

CoRR, 2022

Vector Field Visualization of Single-Qubit State Tomography.

Adrien Suau, Marc Vuffray, Andrey Y. Lokhov, Lukasz Cincio, Carleton Coffrin

Proceedings of the IEEE International Conference on Quantum Computing and Engineering, 2022

2021

Error mitigation with Clifford quantum-circuit data.

Piotr Czarnik, Andrew Arrasmith, Patrick J. Coles, Lukasz Cincio

Quantum, 2021

Effect of barren plateaus on gradient-free optimization.

Andrew Arrasmith, Marco Cerezo, Piotr Czarnik, Lukasz Cincio, Patrick J. Coles

Quantum, 2021

Generalization in quantum machine learning from few training data.

Matthias C. Caro, Hsin-Yuan Huang, Marco Cerezo, Kunal Sharma, Andrew T. Sornborger, Lukasz Cincio, Patrick J. Coles

CoRR, 2021

Can Error Mitigation Improve Trainability of Noisy Variational Quantum Algorithms?

Samson Wang, Piotr Czarnik, Andrew Arrasmith, Marco Cerezo, Lukasz Cincio, Patrick J. Coles

CoRR, 2021

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

M. Bilkis, Marco Cerezo, Guillaume Verdon, Patrick J. Coles, Lukasz Cincio

CoRR, 2021

Layer VQE: A Variational Approach for Combinatorial Optimization on Noisy Quantum Computers.

Xiaoyuan Liu, Anthony Angone, Ruslan Shaydulin, Ilya Safro, Yuri Alexeev, Lukasz Cincio

CoRR, 2021

Long-time simulations with high fidelity on quantum hardware.

Joe Gibbs, Kaitlin Gili, Zoë Holmes, Benjamin Commeau, Andrew Arrasmith, Lukasz Cincio, Patrick J. Coles, Andrew T. Sornborger

CoRR, 2021

2020

An Adaptive Optimizer for Measurement-Frugal Variational Algorithms.

Jonas M. Kübler, Andrew Arrasmith, Lukasz Cincio, Patrick J. Coles

Quantum, 2020

Variational Quantum Fidelity Estimation.

Marco Cerezo, Alexander Poremba, Lukasz Cincio, Patrick J. Coles

Quantum, 2020

Variational Quantum Algorithms.

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

CoRR, 2020

Noise-Induced Barren Plateaus in Variational Quantum Algorithms.

Samson Wang, Enrico Fontana, Marco Cerezo, Kunal Sharma, Akira Sone, Lukasz Cincio, Patrick J. Coles

CoRR, 2020

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

Kunal Sharma, Marco Cerezo, Zoë Holmes, Lukasz Cincio, Andrew T. Sornborger, Patrick J. Coles

CoRR, 2020

Trainability of Dissipative Perceptron-Based Quantum Neural Networks.

Kunal Sharma, Marco Cerezo, Lukasz Cincio, Patrick J. Coles

CoRR, 2020

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

Marco Cerezo, Akira Sone, Tyler Volkoff, Lukasz Cincio, Patrick J. Coles

CoRR, 2020

Learning to Optimize Variational Quantum Circuits to Solve Combinatorial Problems.

Sami Khairy, Ruslan Shaydulin, Lukasz Cincio, Yuri Alexeev, Prasanna Balaprakash

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Reinforcement-Learning-Based Variational Quantum Circuits Optimization for Combinatorial Problems.

Sami Khairy, Ruslan Shaydulin, Lukasz Cincio, Yuri Alexeev, Prasanna Balaprakash

CoRR, 2019