Classical and quantum fingerprinting with shared randomness and one-sided error. - Rolf T. Horn; A. J. Scott; Jonathan Walgate; Richard Cleve; A. I. Lvovsky 001; Barry C. Sanders (Quantum Inf. Comput., 2005)

Quantum-secured blockchain. - Evgeniy O. Kiktenko; Nikolay O. Pozhar; Maxim N. Anufriev; A. S. Trushechkin; R. R. Yunusov; Y. V. Kurochkin; A. I. Lvovsky 001; Aleksey K. Fedorov (CoRR, 2017)

Experimental quantum homodyne tomography via machine learning. - Egor S. Tiunov; V. V. Tiunova; Alexander E. Ulanov; A. I. Lvovsky 001; Aleksey K. Fedorov (CoRR, 2019)

Quantum-inspired annealers as Boltzmann generators for machine learning and statistical physics. - Alexander E. Ulanov; Egor S. Tiunov; A. I. Lvovsky 001 (CoRR, 2019)

End-to-end optical backpropagation for training neural networks. - Xianxin Guo; Thomas D. Barrett; Zhiming M. Wang; A. I. Lvovsky 001 (CoRR, 2019)

Exploratory Combinatorial Optimization with Reinforcement Learning. - Thomas D. Barrett; William R. Clements; Jakob N. Foerster; A. I. Lvovsky 001 (AAAI, 2020)

Interferobot: aligning an optical interferometer by a reinforcement learning agent. - Dmitry Igorevich Sorokin; Alexander E. Ulanov; Ekaterina A. Sazhina; Alexander I. Lvovsky (NeurIPS, 2020)

Engineering Schrödinger cat states with a photonic even-parity detector. - G. S. Thekkadath; B. A. Bell; Ian A. Walmsley; A. I. Lvovsky 001 (Quantum, 2020)

Aligning an optical interferometer with beam divergence control and continuous action space. - Stepan Makarenko; Dmitry Igorevich Sorokin; Alexander E. Ulanov; Alexander I. Lvovsky (CoRL, 2021)

Adaptation of Quadruped Robot Locomotion with Meta-Learning. - Arsen Kuzhamuratov; Dmitry Igorevich Sorokin; Alexander E. Ulanov; A. I. Lvovsky 001 (CoRR, 2021)

Reinforcement learning enhanced quantum-inspired algorithm for combinatorial optimization. - Dmitrii Beloborodov; Alexander E. Ulanov; Jakob N. Foerster; Shimon Whiteson; A. I. Lvovsky 001 (Mach. Learn. Sci. Technol., 2021)

Entangled resource for interfacing single- and dual-rail optical qubits. - David Drahi; Demid V. Sychev; Khurram K. Pirov; Ekaterina A. Sazhina; Valeriy A. Novikov; Ian A. Walmsley; A. I. Lvovsky 001 (Quantum, 2021)

Hybrid training of optical neural networks. - James Spall; Xianxin Guo; Alexander I. Lvovsky (CoRR, 2022)

Autoregressive neural-network wavefunctions for ab initio quantum chemistry. - Thomas D. Barrett; Aleksei O. Malyshev; A. I. Lvovsky 001 (Nat. Mach. Intell., 2022)

Training neural networks with end-to-end optical backpropagation. - James Spall; Xianxin Guo; A. I. Lvovsky 001 (CoRR, 2023)

Roadmap on Neuromorphic Photonics. - Daniel Brunner; Bhavin J. Shastri; Mohammed Al-Qadasi; Hitesh Ballani; Sylvain Barbay; Stefano Biasi; Peter Bienstman; Simon Bilodeau; Wim Bogaerts; Fabian Böhm; Grace Brennan; Sonia M. Buckley; et al. (CoRR, 2025)