Variational quantum one-class classifier by Gunhee Park, Joonsuk Huh, Daniel K Park

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How deep convolutional neural networks lose spatial information with training by Umberto M Tomasini, Leonardo Petrini, Francesco Cagnetta, Matthieu Wyart

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Closed-loop control of a noisy qubit with reinforcement learning by Yongcheng Ding, Xi Chen, Rafael Magdalena-Benedito, José D Martín-Guerrero

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Automated real-space lattice extraction for atomic force microscopy images by Marco Corrias, Lorenzo Papa, Igor Sokolović, Viktor Birschitzky, Alexander Gorfer, Martin Setvin, Michael Schmid, Ulrike Diebold, Michele Reticcioli, Cesare Franchini

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The information of attribute uncertainties: what convolutional neural networks can learn about errors in input data by Natália V N Rodrigues, L Raul Abramo, Nina S T Hirata

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Prediction of the morphological evolution of a splashing drop using an encoder–decoder by Jingzu Yee, Daichi Igarashi(五十嵐大地), Shun Miyatake(宮武駿), Yoshiyuki Tagawa(田川義之)

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Numerical and geometrical aspects of flow-based variational quantum Monte Carlo by James Stokes, Brian Chen, Shravan Veerapaneni

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ELUQuant: event-level uncertainty quantification in deep inelastic scattering by C Fanelli, J Giroux

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Deep learning symmetries and their Lie groups, algebras, and subalgebras from first principles by Roy T Forestano, Konstantin T Matchev, Katia Matcheva, Alexander Roman, Eyup B Unlu, Sarunas Verner

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Generalization of graph-based active learning relaxation strategies across materials by Xiaoxiao Wang, Joseph Musielewicz, Richard Tran, Sudheesh Kumar Ethirajan, Xiaoyan Fu, Hilda Mera, John R Kitchin, Rachel C Kurchin, Zachary W Ulissi

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Differentiable Earth mover’s distance for data compression at the high-luminosity LHC by Rohan Shenoy, Javier Duarte, Christian Herwig, James Hirschauer, Daniel Noonan, Maurizio Pierini, Nhan Tran, Cristina Mantilla Suarez

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Finding simplicity: unsupervised discovery of features, patterns, and order parameters via shift-invariant variational autoencoders by Maxim Ziatdinov, Chun Yin (Tommy) Wong, Sergei V Kalinin

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Rescuing off-equilibrium simulation data through dynamic experimental data with dynAMMo by Christopher Kolloff, Simon Olsson

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Regression transients modeling of solid rocket motor burning surfaces with physics-guided neural network by XueQin Sun, Yu Li, YiHong Li, SuKai Wang, Xuan Li, Ming Lu, Ping Chen

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Manifold learning in atomistic simulations: a conceptual review by Jakub Rydzewski, Ming Chen, Omar Valsson

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Theoretical characterization of uncertainty in high-dimensional linear classification by Lucas Clarté, Bruno Loureiro, Florent Krzakala, Lenka Zdeborová

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Conditioning Boltzmann generators for rare event sampling by Sebastian Falkner, Alessandro Coretti, Salvatore Romano, Phillip L Geissler, Christoph Dellago

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Governing equation discovery based on causal graph for nonlinear dynamic systems by Dongni Jia, Xiaofeng Zhou, Shuai Li, Shurui Liu, Haibo Shi

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Machine-learning Kohn–Sham potential from dynamics in time-dependent Kohn–Sham systems by Jun Yang, James Whitfield

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Classifying rock types by geostatistics and random forests in tandem by Parag Jyoti Dutta, Xavier Emery

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