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)

Trainability barriers and opportunities in quantum generative modeling. - Manuel S. Rudolph; Sacha Lerch; Supanut Thanasilp; Oriel Kiss; Sofia Vallecorsa; Michele Grossi; Zoë Holmes (CoRR, 2023)

Does provable absence of barren plateaus imply classical simulability? Or, why we need to rethink variational quantum computing. - Marco Cerezo; Martin Larocca; Diego García-Martín; Nelson L. Diaz; Paolo Braccia; Enrico Fontana; Manuel S. Rudolph; Pablo Bermejo 002; Aroosa Ijaz; Supanut Thanasilp; Eric R. Anschütz; Zoë Holmes (CoRR, 2023)

Data re-uploading with a single qudit. - Noah L. Wach; Manuel S. Rudolph; Fred Jendrzejewski; Sebastian Schmitt (Quantum Mach. Intell., 2023)

Quantum Convolutional Neural Networks are (Effectively) Classically Simulable. - Pablo Bermejo 002; Paolo Braccia; Manuel S. Rudolph; Zoë Holmes; Lukasz Cincio; Marco Cerezo (CoRR, 2024)

Classically estimating observables of noiseless quantum circuits. - Armando Angrisani; Alexander Schmidhuber; Manuel S. Rudolph; Marco Cerezo; Zoë Holmes; Hsin-Yuan Huang (CoRR, 2024)

Efficient quantum-enhanced classical simulation for patches of quantum landscapes. - Sacha Lerch; Ricard Puig-i-Valls; Manuel S. Rudolph; Armando Angrisani; Tyson Jones; Marco Cerezo; Supanut Thanasilp; Zoë Holmes (CoRR, 2024)

A unifying account of warm start guarantees for patches of quantum landscapes. - Hela Mhiri; Ricard Puig-i-Valls; Sacha Lerch; Manuel S. Rudolph; Thiparat Chotibut; Supanut Thanasilp; Zoë Holmes (CoRR, 2025)