Automation of quantum dot measurement analysis via explainable machine learning by Daniel Schug, Tyler J Kovach, M A Wolfe, Jared Benson, Sanghyeok Park, J P Dodson, J Corrigan, M A Eriksson, Justyna P Zwolak

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Discovering emergent connections in quantum physics research via dynamic word embeddings by Felix Frohnert, Xuemei Gu, Mario Krenn, Evert van Nieuwenburg

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Advancing privacy-aware machine learning on sensitive data via edge-based continual µ-training for personalized large models by Zhaojing Huang, Leping Yu, Luis Fernando Herbozo Contreras, Kamran Eshraghian, Nhan Duy Truong, Armin Nikpour, Omid Kavehei

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Laryngeal cancer diagnosis based on improved YOLOv8 algorithm by Xin Nie, Xueyan Zhang, Di Wang, Yuankun Liu, Lumin Xing, Wenjian Liu

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Closed-form interpretation of neural network classifiers with symbolic gradients by Sebastian J Wetzel

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Asymptotically stable data-driven koopman operator approximation with inputs using total extended DMD by Louis Lortie, James Richard Forbes

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AtOMICS: a deep learning-based automated optomechanical intelligent coupling system for testing and characterization of silicon photonics chiplets by Jaime Gonzalo Flor Flores, Jim Solomon, Connor Nasseraddin, Talha Yerebakan, Andrey B Matsko, Chee Wei Wong

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SymbolNet: neural symbolic regression with adaptive dynamic pruning for compression by Ho Fung Tsoi, Vladimir Loncar, Sridhara Dasu, Philip Harris

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An autoencoder for compressing angle-resolved photoemission spectroscopy data by Steinn Ýmir Ágústsson, Mohammad Ahsanul Haque, Thi Tam Truong, Marco Bianchi, Nikita Klyuchnikov, Davide Mottin, Panagiotis Karras, Philip Hofmann

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Stochastic black-box optimization using multi-fidelity score function estimator by Atul Agrawal, Kislaya Ravi, Phaedon-Stelios Koutsourelakis, Hans-Joachim Bungartz

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Predicting nonequilibrium Green’s function dynamics and photoemission spectra via nonlinear integral operator learning by Yuanran Zhu, Jia Yin, Cian C Reeves, Chao Yang, Vojtěch Vlček

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Efficient Monte Carlo simulation of streamer discharges with deep-learning denoising models by F M Bayo-Muñoz, A Malagón-Romero, A Luque

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Characterizing out-of-distribution generalization of neural networks: application to the disordered Su–Schrieffer–Heeger model by Kacper Cybiński, Marcin Płodzień, Michał Tomza, Maciej Lewenstein, Alexandre Dauphin, Anna Dawid

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rule4ml: an open-source tool for resource utilization and latency estimation for ML models on FPGA by Mohammad Mehdi Rahimifar, Hamza Ezzaoui Rahali, Audrey C Therrien

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Large language models for causal hypothesis generation in science by Kai-Hendrik Cohrs, Emiliano Diaz, Vasileios Sitokonstantinou, Gherardo Varando, Gustau Camps-Valls

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Are queries and keys always relevant? A case study on transformer wave functions by Riccardo Rende, Luciano Loris Viteritti

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Evaluating machine learning models for supernova gravitational wave signal classification by Y Sultan Abylkairov, Matthew C Edwards, Daniil Orel, Ayan Mitra, Bekdaulet Shukirgaliyev, Ernazar Abdikamalov

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QR-DeepONet: resolve abnormal convergence issue in deep operator network by Jie Zhao, Biwei Xie, Xingquan Li

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Incorporating edge convolution and correlative self-attention into graph neural network for material properties prediction by Zexi Yang, Qi Yu, Yapeng Zhan, Jiying Liu

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A novel dynamic machine learning-based explainable fusion monitoring: application to industrial and chemical processes by Husnain Ali, Rizwan Safdar, Yuanqiang Zhou, Yuan Yao, Le Yao, Zheng Zhang, Weilong Ding, Furong Gao

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