Lukasz Cincio - RankMe

44 papers A* 1Misc 3Journal 40

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Quantum Circuit Pre-Synthesis: Learning Local Edits to Reduce T-count. CoRR Daniele Lizzio Bosco, Lukasz Cincio, Giuseppe Serra, Marco Cerezo
2025	J	`jnl`	Deep Circuit Compression for Quantum Dynamics via Tensor Networks. Quantum Joe Gibbs, Lukasz Cincio
2025	J	`jnl`	Improving the efficiency of learning-based error mitigation. Quantum Piotr Czarnik, Michael M. McKerns, Andrew T. Sornborger, Lukasz Cincio
2024	J	`jnl`	A Review of Barren Plateaus in Variational Quantum Computing. CoRR Martin Larocca, Supanut Thanasilp, Samson Wang, Kunal Sharma, Jacob D. Biamonte, Patrick J. Coles, Lukasz Cincio, Jarrod R. McClean, Zoë Holmes, Marco Cerezo
2024	J	`jnl`	Can Error Mitigation Improve Trainability of Noisy Variational Quantum Algorithms? Quantum Samson Wang, Piotr Czarnik, Andrew Arrasmith, Marco Cerezo, Lukasz Cincio, Patrick J. Coles
2024	J	`jnl`	Computing exact moments of local random quantum circuits via tensor networks. Quantum Mach. Intell. Paolo Braccia, Pablo Bermejo, Lukasz Cincio, Marco Cerezo
2024	J	`jnl`	Exact spectral gaps of random one-dimensional quantum circuits. CoRR Andrew E. Deneris, Pablo Bermejo, Paolo Braccia, Lukasz Cincio, Marco Cerezo
2024	J	`jnl`	On the practical usefulness of the Hardware Efficient Ansatz. Quantum Lorenzo Leone, Salvatore F. E. Oliviero, Lukasz Cincio, Marco Cerezo
2024	J	`jnl`	Quantum Convolutional Neural Networks are (Effectively) Classically Simulable. CoRR Pablo Bermejo, Paolo Braccia, Manuel S. Rudolph, Zoë Holmes, Lukasz Cincio, Marco Cerezo
2024	J	`jnl`	Scalable quantum dynamics compilation via quantum machine learning. CoRR Yuxuan Zhang, Roeland Wiersema, Juan Carrasquilla, Lukasz Cincio, Yong Baek Kim
2023	J	`jnl`	A semi-agnostic ansatz with variable structure for variational quantum algorithms. Quantum Mach. Intell. Matías Bilkis, Marco Cerezo, Guillaume Verdon, Patrick J. Coles, Lukasz Cincio
2023	J	`jnl`	Challenges and Opportunities in Quantum Machine Learning. CoRR Marco Cerezo, Guillaume Verdon, Hsin-Yuan Huang, Lukasz Cincio, Patrick J. Coles
2023	Misc	`conf`	QFactor: A Domain-Specific Optimizer for Quantum Circuit Instantiation. QCE Alon Kukliansky, Ed Younis, Lukasz Cincio, Costin Iancu
2023	J	`jnl`	Scaling Whole-Chip QAOA for Higher-Order Ising Spin Glass Models on Heavy-Hex Graphs. CoRR Elijah Pelofske, Andreas Bärtschi, Lukasz Cincio, John Golden, Stephan J. Eidenbenz
2023	Misc	`conf`	Single-Qubit Cross Platform Comparison of Quantum Computing Hardware. QCE Adrien Suau, Jon Nelson, Marc Vuffray, Andrey Y. Lokhov, Lukasz Cincio, Carleton Coffrin
2023	J	`jnl`	The battle of clean and dirty qubits in the era of partial error correction. Quantum Daniel Bultrini, Samson Wang, Piotr Czarnik, Max Hunter Gordon, Marco Cerezo, Patrick J. Coles, Lukasz Cincio
2023	J	`jnl`	Unifying and benchmarking state-of-the-art quantum error mitigation techniques. Quantum Daniel Bultrini, Max Hunter Gordon, Piotr Czarnik, Andrew Arrasmith, Marco Cerezo, Patrick J. Coles, Lukasz Cincio
2023	J	`jnl`	Variational Quantum Linear Solver. Quantum Carlos Bravo-Prieto, Ryan LaRose, Marco Cerezo, Yigit Subasi, Lukasz Cincio, Patrick J. Coles
2022	J	`jnl`	Challenges and opportunities in quantum machine learning. Nat. Comput. Sci. Marco Cerezo, Guillaume Verdon, Hsin-Yuan Huang, Lukasz Cincio, Patrick J. Coles
2022	J	`jnl`	Covariance matrix preparation for quantum principal component analysis. CoRR Max Hunter Gordon, Marco Cerezo, Lukasz Cincio, Patrick J. Coles
2022	J	`jnl`	Dynamical simulation via quantum machine learning with provable generalization. CoRR Joe Gibbs, Zoë Holmes, Matthias C. Caro, Nicholas Ezzell, Hsin-Yuan Huang, Lukasz Cincio, Andrew T. Sornborger, Patrick J. Coles
2022	J	`jnl`	Out-of-distribution generalization for learning quantum dynamics. CoRR Matthias C. Caro, Hsin-Yuan Huang, Nicholas Ezzell, Joe Gibbs, Andrew T. Sornborger, Lukasz Cincio, Patrick J. Coles, Zoë Holmes
2022	J	`jnl`	Practical Black Box Hamiltonian Learning. CoRR Andi Gu, Lukasz Cincio, Patrick J. Coles
2022	J	`jnl`	Resource frugal optimizer for quantum machine learning. CoRR Charles Moussa, Max Hunter Gordon, Michal Baczyk, Marco Cerezo, Lukasz Cincio, Patrick J. Coles
2022	Misc	`conf`	Vector Field Visualization of Single-Qubit State Tomography. QCE Adrien Suau, Marc Vuffray, Andrey Y. Lokhov, Lukasz Cincio, Carleton Coffrin
2021	J	`jnl`	A semi-agnostic ansatz with variable structure for quantum machine learning. CoRR Matías Bilkis, Marco Cerezo, Guillaume Verdon, Patrick J. Coles, Lukasz Cincio
2021	J	`jnl`	Can Error Mitigation Improve Trainability of Noisy Variational Quantum Algorithms? CoRR Samson Wang, Piotr Czarnik, Andrew Arrasmith, Marco Cerezo, Lukasz Cincio, Patrick J. Coles
2021	J	`jnl`	Effect of barren plateaus on gradient-free optimization. Quantum Andrew Arrasmith, Marco Cerezo, Piotr Czarnik, Lukasz Cincio, Patrick J. Coles
2021	J	`jnl`	Error mitigation with Clifford quantum-circuit data. Quantum Piotr Czarnik, Andrew Arrasmith, Patrick J. Coles, Lukasz Cincio
2021	J	`jnl`	Generalization in quantum machine learning from few training data. CoRR Matthias C. Caro, Hsin-Yuan Huang, Marco Cerezo, Kunal Sharma, Andrew T. Sornborger, Lukasz Cincio, Patrick J. Coles
2021	J	`jnl`	Layer VQE: A Variational Approach for Combinatorial Optimization on Noisy Quantum Computers. CoRR Xiaoyuan Liu, Anthony Angone, Ruslan Shaydulin, Ilya Safro, Yuri Alexeev, Lukasz Cincio
2021	J	`jnl`	Long-time simulations with high fidelity on quantum hardware. CoRR Joe Gibbs, Kaitlin Gili, Zoë Holmes, Benjamin Commeau, Andrew Arrasmith, Lukasz Cincio, Patrick J. Coles, Andrew T. Sornborger
2020	J	`jnl`	An Adaptive Optimizer for Measurement-Frugal Variational Algorithms. Quantum Jonas M. Kübler, Andrew Arrasmith, Lukasz Cincio, Patrick J. Coles
2020	J	`jnl`	Cost-Function-Dependent Barren Plateaus in Shallow Quantum Neural Networks. CoRR Marco Cerezo, Akira Sone, Tyler J. Volkoff, Lukasz Cincio, Patrick J. Coles
2020	J	`jnl`	Effect of barren plateaus on gradient-free optimization. CoRR Andrew Arrasmith, Marco Cerezo, Piotr Czarnik, Lukasz Cincio, Patrick J. Coles
2020	A*	`conf`	Learning to Optimize Variational Quantum Circuits to Solve Combinatorial Problems. AAAI Sami Khairy, Ruslan Shaydulin, Lukasz Cincio, Yuri Alexeev, Prasanna Balaprakash
2020	J	`jnl`	Noise-Induced Barren Plateaus in Variational Quantum Algorithms. CoRR Samson Wang, Enrico Fontana, Marco Cerezo, Kunal Sharma, Akira Sone, Lukasz Cincio, Patrick J. Coles
2020	J	`jnl`	Reformulation of the No-Free-Lunch Theorem for Entangled Data Sets. CoRR Kunal Sharma, Marco Cerezo, Zoë Holmes, Lukasz Cincio, Andrew T. Sornborger, Patrick J. Coles
2020	J	`jnl`	Trainability of Dissipative Perceptron-Based Quantum Neural Networks. CoRR Kunal Sharma, Marco Cerezo, Lukasz Cincio, Patrick J. Coles
2020	J	`jnl`	Variational Quantum Algorithms. CoRR 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
2020	J	`jnl`	Variational Quantum Fidelity Estimation. Quantum Marco Cerezo, Alexander Poremba, Lukasz Cincio, Patrick J. Coles
2019	J	`jnl`	Learning to Optimize Variational Quantum Circuits to Solve Combinatorial Problems. CoRR Sami Khairy, Ruslan Shaydulin, Lukasz Cincio, Yuri Alexeev, Prasanna Balaprakash
2019	J	`jnl`	Quantum-assisted quantum compiling. Quantum Sumeet Khatri, Ryan LaRose, Alexander Poremba, Lukasz Cincio, Andrew T. Sornborger, Patrick J. Coles
2019	J	`jnl`	Reinforcement-Learning-Based Variational Quantum Circuits Optimization for Combinatorial Problems. CoRR Sami Khairy, Ruslan Shaydulin, Lukasz Cincio, Yuri Alexeev, Prasanna Balaprakash