Solving Quantum Chemistry Problems with a D-Wave Quantum Annealer. - Michael Streif; Florian Neukart; Martin Leib (QTOP@NetSys, 2017)

TensorFlow Quantum: A Software Framework for Quantum Machine Learning. - Michael Broughton; Guillaume Verdon; Trevor McCourt; Antonio J. Martinez; Jae Hyeon Yoo; Sergei V. Isakov; Philip Massey; Murphy Yuezhen Niu; Ramin Halavati; Evan Peters; Martin Leib; Andrea Skolik; et al. (CoRR, 2020)

Solving the Shipment Rerouting Problem with Quantum Optimization Techniques. - Sheir Yarkoni; Andreas Huck; Hanno Schülldorf; Benjamin Speitkamp; Marc Shakory Tabrizi; Martin Leib; Thomas Bäck; Florian Neukart (ICCL, 2021)

Layerwise learning for quantum neural networks. - Andrea Skolik; Jarrod R. McClean; Masoud Mohseni; Patrick van der Smagt; Martin Leib (Quantum Mach. Intell., 2021)

Workshop Summary: Quantum Machine Learning. - Volker Tresp; Steffen Udluft; Daniel Hein 001; Werner Hauptmann; Martin Leib; Christopher Mutschler; Daniel D. Scherer; Wolfgang Mauerer (QCE, 2023)

Small Quantum Codes from Algebraic Extensions of Generalized Bicycle Codes. - Nikolaos Koukoulekidis; Fedor Simkovic IV; Martin Leib; Francisco Revson Fernandes Pereira (CoRR, 2024)

Low-depth simulations of fermionic systems on square-grid quantum hardware. - Manuel G. Algaba; P. V. Sriluckshmy; Martin Leib; Fedor Simkovic IV (Quantum, 2024)

Vanishing performance of the parity-encoded quantum approximate optimization algorithm applied to spin-glass models. - Elisabeth Wybo; Martin Leib (Quantum, 2024)