GRINN: a physics-informed neural network for solving hydrodynamic systems in the presence of self-gravity by Sayantan Auddy, Ramit Dey, Neal J Turner, Shantanu Basu

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Analysis and Benchmarking of feature reduction for classification under computational constraints by Omer Subasi, Sayan Ghosh, Joseph Manzano, Bruce Palmer, Andrés Marquez

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Improving cross-subject classification performance of motor imagery signals: a data augmentation-focused deep learning framework by Enes Ozelbas, Emine Elif Tülay, Serhat Ozekes

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Qudit machine learning by Sebastián Roca-Jerat, Juan Román-Roche, David Zueco

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Realistic mask generation for matter-wave lithography via machine learning by Johannes Fiedler, Adriá Salvador Palau, Eivind Kristen Osestad, Pekka Parviainen, Bodil Holst

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Scalable quantum measurement error mitigation via conditional independence and transfer learning by Changwon Lee, Daniel K Park

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GA-based weighted ensemble learning for multi-label aerial image classification using convolutional neural networks and vision transformers by Ming-Hseng Tseng

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Time-warping invariant quantum recurrent neural networks via quantum-classical adaptive gating by Ivana Nikoloska, Osvaldo Simeone, Leonardo Banchi, Petar Veličković

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Generative adversarial networks for data-scarce radiative heat transfer applications by J J García-Esteban, J C Cuevas, J Bravo-Abad

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Comment on ‘Physics-based representations for machine learning properties of chemical reactions’ by Kevin A Spiekermann, Thijs Stuyver, Lagnajit Pattanaik, William H Green

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Recipes for when physics fails: recovering robust learning of physics informed neural networks by Chandrajit Bajaj, Luke McLennan, Timothy Andeen, Avik Roy

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Data-driven plasma modelling: surrogate collisional radiative models of fluorocarbon plasmas from deep generative autoencoders by G A Daly, J E Fieldsend, G Hassall, G R Tabor

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Fast neural network inference on FPGAs for triggering on long-lived particles at colliders by Andrea Coccaro, Francesco Armando Di Bello, Stefano Giagu, Lucrezia Rambelli, Nicola Stocchetti

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Neural network enhanced measurement efficiency for molecular groundstates by Dmitri Iouchtchenko, Jérôme F Gonthier, Alejandro Perdomo-Ortiz, Roger G Melko

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Estimating truncation effects of quantum bosonic systems using sampling algorithms by Masanori Hanada, Junyu Liu, Enrico Rinaldi, Masaki Tezuka

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The reusability prior: comparing deep learning models without training by Aydın Göze Polat, Ferda Nur Alpaslan

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Plug & play directed evolution of proteins with gradient-based discrete MCMC by Patrick Emami, Aidan Perreault, Jeffrey Law, David Biagioni, Peter St. John

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Equivariant neural networks for spin dynamics simulations of itinerant magnets by Yu Miyazaki

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Laziness, barren plateau, and noises in machine learning by Junyu Liu, Zexi Lin, Liang Jiang

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Looking at the posterior: accuracy and uncertainty of neural-network predictions by Hampus Linander, Oleksandr Balabanov, Henry Yang, Bernhard Mehlig

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