Quantum unsupervised and supervised learning on superconducting processors. - Abhijat Sarma; Rupak Chatterjee; Kaitlin Gili; Ting Yu 006 (Quantum Inf. Comput., 2020)

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)

Evaluating Generalization in Classical and Quantum Generative Models. - Kaitlin Gili; Marta Mauri; Alejandro Perdomo-Ortiz (CoRR, 2022)

Introducing Non-Linearity into Quantum Generative Models. - Kaitlin Gili; Mykolas Sveistrys; Chris Ballance (CoRR, 2022)

Do Quantum Circuit Born Machines Generalize? - Kaitlin Gili; Mohamed Hibat-Allah; Marta Mauri; Chris Ballance; Alejandro Perdomo-Ortiz (CoRR, 2022)

Generative Modeling with Quantum Neurons. - Kaitlin Gili; Rohan S. Kumar; Mykolas Sveistrys; C. J. Ballance (CoRR, 2023)

An inductive bias from quantum mechanics: learning order effects with non-commuting measurements. - Kaitlin Gili; Guillermo Alonso; Maria Schuld (Quantum Mach. Intell., 2024)

Discovering group dynamics in coordinated time series via hierarchical recurrent switching-state models. - Michael T. Wojnowicz; Kaitlin Gili; Preetish Rath; Eric L. Miller 001; Jeffrey Miller; Clifford Hancock; Meghan O'Donovan; Seth Elkin-Frankston; Tad Brunyé; Michael C. Hughes (Trans. Mach. Learn. Res., 2025)

Using machine learning to measure evidence of students' sensemaking in physics courses. - Kaitlin Gili; Kyle Heuton; Astha Shah; Michael C. Hughes (CoRR, 2025)