Efficient Learning for Deep Quantum Neural Networks. - Kerstin Beer; Dmytro Bondarenko; Terry Farrelly; Tobias J. Osborne; Robert Salzmann; Ramona Wolf (CoRR, 2019)

Symmetric distinguishability as a quantum resource. - Robert Salzmann; Nilanjana Datta; Gilad Gour; Xin Wang 022; Mark M. Wilde (CoRR, 2021)

Interpolating between symmetric and asymmetric hypothesis testing. - Robert Salzmann; Nilanjana Datta (CoRR, 2021)

Total insecurity of communication via strong converse for quantum privacy amplification. - Robert Salzmann; Nilanjana Datta (CoRR, 2022)

Learning Quantum Processes with Memory - Quantum Recurrent Neural Networks. - Dmytro Bondarenko; Robert Salzmann; Viktoria-S. Schmiesing (CoRR, 2023)

Sample complexity of quantum hypothesis testing. - Hao-Chung Cheng; Nilanjana Datta; Nana Liu; Theshani Nuradha; Robert Salzmann; Mark M. Wilde (CoRR, 2024)

Convergence rates for the Trotter-Kato splitting. - Simon Becker; Niklas Galke; Robert Salzmann; Lauritz van Luijk (CoRR, 2024)

Parallelization of Adaptive Quantum Channel Discrimination in the Non-Asymptotic Regime. - Bjarne Berg; Nilanjana Datta; Robert Salzmann; Mark M. Wilde (IEEE Trans. Inf. Theory, 2024)