Reinforcement Learning Assisted Recursive QAOA. - Yash J. Patel; Sofiène Jerbi; Thomas Bäck; Vedran Dunjko (CoRR, 2022)

Enhancing variational quantum state diagonalization using reinforcement learning techniques. - Akash Kundu; Przemyslaw Bedelek; Mateusz Ostaszewski; Onur Danaci; Yash J. Patel; Vedran Dunjko; Jaroslaw Adam Miszczak (CoRR, 2023)

Curriculum reinforcement learning for quantum architecture search under hardware errors. - Yash J. Patel; Akash Kundu; Mateusz Ostaszewski; Xavier Bonet-Monroig; Vedran Dunjko; Onur Danaci (ICLR, 2024)

An Adaptive Re-evaluation Method for Evolution Strategy under Additive Noise. - Catalin-Viorel Dinu; Yash J. Patel; Xavier Bonet-Monroig; Hao Wang (CoRR, 2024)

Hyperparameter importance and optimization of quantum neural networks across small datasets. - Charles Moussa; Yash J. Patel; Vedran Dunjko; Thomas Bäck; Jan N. van Rijn (Mach. Learn., 2024)

An Adaptive Re-evaluation Method for Evolution Strategy under Additive Noise. - Catalin-Viorel Dinu; Yash J. Patel; Xavier Bonet-Monroig; Hao Wang 025 (GECCO, 2025)

Evolving Hard Maximum Cut Instances for Quantum Approximate Optimization Algorithms. - Shuaiqun Pan; Yash J. Patel; Aneta Neumann; Frank Neumann 001; Thomas Bäck; Hao Wang 025 (GECCO, 2025)