Test Generation and Fault Localization for Quantum Circuits. - Marek A. Perkowski; Jacob D. Biamonte; Martin Lukac (ISMVL, 2005)

The Cost of Quantum Gate Primitives. - Soonchil Lee; Seong-Joo Lee; Taegon Kim; Jae-Seung Lee; Jacob D. Biamonte; Marek A. Perkowski (J. Multiple Valued Log. Soft Comput., 2006)

Four-level realisation of 3-qubit reversible functions. - Guowu Yang; Xiaoyu Song; Marek A. Perkowski; William N. N. Hung; Jacob D. Biamonte; Zhiwei Tang (IET Comput. Digit. Tech., 2007)

The Computational Power of Minkowski Spacetime - Jacob D. Biamonte (CoRR, 2009)

Categorical Tensor Network States - Jacob D. Biamonte; Stephen R. Clark; Dieter Jaksch (CoRR, 2010)

Fault Models for Quantum Mechanical Switching Networks. - Jacob D. Biamonte; Jeff S. Allen; Marek A. Perkowski (J. Electron. Test., 2010)

Tensor Network Contractions for #SAT. - Jacob D. Biamonte; Jason Morton; Jacob W. Turner (CoRR, 2014)

Tensor networks and graphical calculus for open quantum systems. - Christopher J. Wood; Jacob D. Biamonte; David G. Cory (Quantum Inf. Comput., 2015)

Complex Networks: from Classical to Quantum. - Jacob D. Biamonte; Mauro Faccin; Manlio De Domenico (CoRR, 2017)

Quantum machine learning. - Jacob D. Biamonte; Peter Wittek; Nicola Pancotti; Patrick Rebentrost; Nathan Wiebe; Seth Lloyd (Nat., 2017)

Quantum Machine Learning Matrix Product States. - Jacob D. Biamonte (CoRR, 2018)

Quantum Supremacy Lower Bounds by Entanglement Scaling. - Jacob D. Biamonte; Mauro E. S. Morales; Dax Enshan Koh (CoRR, 2018)

Deep Learning Super-Diffusion in Multiplex Networks. - Vito M. Leli; Saeed Osat; Timur Tlyachev; Jacob D. Biamonte (CoRR, 2018)

Experimental neural network enhanced quantum tomography. - Adriano Macarone Palmieri; Egor Kovlakov; Federico Bianchi 001; Dmitry Yudin; Stanislav Straupe; Jacob D. Biamonte; Sergei Kulik (CoRR, 2019)

Machine Learning Phase Transitions with a Quantum Processor. - Alexey Uvarov; Andrey Kardashin; Jacob D. Biamonte (CoRR, 2019)

Computational Phase Transition Signature in Gibbs Sampling. - H. Philathong; Vishwanathan Akshay; Igor Zacharov; Jacob D. Biamonte (CoRR, 2019)

Reachability Deficits in Quantum Approximate Optimization. - Vishwanathan Akshay; H. Philathong; Mauro E. S. Morales; Jacob D. Biamonte (CoRR, 2019)

Variational Quantum Eigensolver for Frustrated Quantum Systems. - Alexey Uvarov; Jacob D. Biamonte; Dmitry Yudin (CoRR, 2020)

Probing Criticality in Quantum Spin Chains with Neural Networks. - A. Berezutskii; M. Beketov; Dmitry Yudin; Zoltán Zimborás; Jacob D. Biamonte (CoRR, 2020)

Self-learning eigenstates with a quantum processor. - Andrey Kardashin; Alexey Uvarov; Dmitry Yudin; Jacob D. Biamonte (CoRR, 2020)

Unraveling the effects of multiscale network entanglement on disintegration of empirical systems. - Arsham Ghavasieh; Massimo Stella; Jacob D. Biamonte; Manlio De Domenico (CoRR, 2020)

On the Theory of Modern Quantum Algorithms. - Jacob D. Biamonte (CoRR, 2020)

On barren plateaus and cost function locality in variational quantum algorithms. - Alexey Uvarov; Jacob D. Biamonte (CoRR, 2020)

On the universality of the quantum approximate optimization algorithm. - Mauro E. S. Morales; Jacob D. Biamonte; Zoltán Zimborás (Quantum Inf. Process., 2020)

Training Saturation in Layerwise Quantum Approximate Optimisation. - Ernesto Campos; Daniil Rabinovich; Vishwanathan Akshay; Jacob D. Biamonte (CoRR, 2021)

Reachability Deficits in Quantum Approximate Optimization of Graph Problems. - Vishwanathan Akshay; H. Philathong; Igor Zacharov; Jacob D. Biamonte (Quantum, 2021)

On Circuit Depth Scaling For Quantum Approximate Optimization. - Vishwanathan Akshay; H. Philathong; E. Campos; Daniil Rabinovich; Igor Zacharov; Xiao-Ming Zhang; Jacob D. Biamonte (CoRR, 2022)

Quantum machine learning channel discrimination. - Andrey Kardashin; Anna Vlasova; Anastasia Pervishko; Dmitry Yudin; Jacob D. Biamonte (CoRR, 2022)

Tensor networks in machine learning. - Richik Sengupta; Soumik Adhikary; Ivan V. Oseledets; Jacob D. Biamonte (CoRR, 2022)

On Symmetric Pseudo-Boolean Functions: Factorization, Kernels and Applications. - Richik Sengupta; Jacob D. Biamonte (CoRR, 2022)

Experimental quantum adversarial learning with programmable superconducting qubits. - Wenhui Ren; Weikang Li; Shibo Xu; Ke Wang; Wenjie Jiang; Feitong Jin; Xuhao Zhu; Jiachen Chen; Zixuan Song; Pengfei Zhang; Hang Dong; Xu Zhang; et al. (Nat. Comput. Sci., 2022)

Construction of a Circuit for the Simulation of a Hamiltonian with a Tridiagonal Matrix Representation. - Boris Arseniev; Dmitry Guskov; Richik Sengupta; Jacob D. Biamonte; Igor Zacharov (CoRR, 2023)

A Review of Barren Plateaus in Variational Quantum Computing. - Martin Larocca; Supanut Thanasilp; Samson Wang; Kunal Sharma; Jacob D. Biamonte; Patrick J. Coles; Lukasz Cincio; Jarrod R. McClean; Zoë Holmes; Marco Cerezo (CoRR, 2024)