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)

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)

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)

The power and limitations of learning quantum dynamics incoherently. - Sofiène Jerbi; Joe Gibbs; Manuel S. Rudolph; Matthias C. Caro; Patrick J. Coles; Hsin-Yuan Huang; Zoë Holmes (CoRR, 2023)

Deep Circuit Compression for Quantum Dynamics via Tensor Networks. - Joe Gibbs; Lukasz Cincio (Quantum, 2025)

Multi-Target Radar Search and Track Using Sequence-Capable Deep Reinforcement Learning. - Jan-Hendrik Ewers; David Cormack; Joe Gibbs; David Anderson 005 (CoRR, 2025)

Stone Soup Multi-Target Tracking Feature Extraction For Autonomous Search And Track In Deep Reinforcement Learning Environment. - Jan-Hendrik Ewers; Joe Gibbs; David Anderson 005 (CoRR, 2025)

Exploiting symmetries in nuclear Hamiltonians for ground state preparation. - Joe Gibbs; Zoë Holmes; Paul Stevenson (Quantum Mach. Intell., 2025)