Shuang Cong, Chenyu Su, “Reconstructing quantum states with VAE and CVAE”, Quantum Mach. Intell., 7:1 (2025)
Bowen Hou, Jinyuan Wu, Victor Chang Lee, Jiaxuan Guo, Luna Y. Liu, Diana Y. Qiu, “Data-driven low-rank approximation for the electron-hole kernel and acceleration of time-dependent GW calculations”, npj Comput Mater, 11:1 (2025)
Andrea Pollastro, Francesco Isgrò, Roberto Prevete, “SincVAE: A new semi-supervised approach to improve anomaly detection on EEG data using SincNet and variational autoencoder”, Computer Methods and Programs in Biomedicine Update, 2025, 100213
Lingxia Zhang, Xiaodie Lin, Peidong Wang, Kaiyan Yang, Xiao Zeng, Zhaohui Wei, Zizhu Wang, “Variational optimization for quantum problems using deep generative networks”, Commun Phys, 8:1 (2025)
Federico Succetti, Massimo Panella, Paolo Giannitrapani, Jean-Christophe Rigo, Stefania Colonnese, “Machine Learning for Fluid Thermodynamics: State of the Art and Open Challenges”, IEEE Access, 13 (2025), 171073
Farina Riaz, Fakhar Zaman, Hajime Suzuki, Alsharif Abuadbba, David Nguyen, “Quantum Down-Sampling Filter for Variational Autoencoder”, Electronics, 14:23 (2025), 4626
Denis A. Kulikov, Vsevolod I. Yashin, Aleksey K. Fedorov, Evgeniy O. Kiktenko, “Minimizing the negativity of quantum circuits in overcomplete quasiprobability representations”, Phys. Rev. A, 109:1 (2024)
Antonio Ciarlo, David Bronte Ciriza, Martin Selin, Onofrio M. Maragò, Antonio Sasso, Giuseppe Pesce, Giovanni Volpe, Mattias Goksör, “Deep learning for optical tweezers”, Nanophotonics, 13:17 (2024), 3017
Yanming Che, Clemens Gneiting, Franco Nori, “Exponentially improved efficient machine learning for quantum many-body states with provable guarantees”, Phys. Rev. Research, 6:3 (2024)
Jingyang Zheng, Han Kheng Teoh, Michelle L. Delco, Lawrence J. Bonassar, Itai Cohen, Mohamed Yacin Sikkandar, “Application of a variational autoencoder for clustering and analyzing in situ articular cartilage cellular response to mechanical stimuli”, PLoS ONE, 19:5 (2024), e0297947