Exploring explainable AI: category theory insights into machine learning algorithms by Ares Fabregat-Hernández, Javier Palanca, Vicent Botti

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Standardizing chemical compounds with language models by Miruna T Cretu, Alessandra Toniato, Amol Thakkar, Amin A Debabeche, Teodoro Laino, Alain C Vaucher

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Data efficiency and extrapolation trends in neural network interatomic potentials by Joshua A Vita, Daniel Schwalbe-Koda

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MS2OD: outlier detection using minimum spanning tree and medoid selection by Jia Li, Jiangwei Li, Chenxu Wang, Fons J Verbeek, Tanja Schultz, Hui Liu

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Autonomous data extraction from peer reviewed literature for training machine learning models of oxidation potentials by Siwoo Lee, Stefan Heinen, Danish Khan, O Anatole von Lilienfeld

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Machine-learning approach for quantified resolvability enhancement of low-dose STEM data by Laura Gambini, Tiarnan Mullarkey, Lewys Jones, Stefano Sanvito

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Massively parallel fitting of Gaussian approximation potentials by Sascha Klawohn, James R Kermode, Albert P Bartók

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Adaptive sampling for accelerating neutron diffraction-based strain mapping by S V Venkatakrishnan, Chris M Fancher, Maxim Ziatdinov, Rama Vasudevan, Kyle Saleeby, James Haley, Dunji Yu, Ke An, Alex Plotkowski

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Noise-aware physics-informed machine learning for robust PDE discovery by Pongpisit Thanasutives, Takashi Morita, Masayuki Numao, Ken-ichi Fukui

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Investigation of inverse design of multilayer thin-films with conditional invertible neural networks by Alexander Luce, Ali Mahdavi, Heribert Wankerl, Florian Marquardt

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A detailed study of interpretability of deep neural network based top taggers by Ayush Khot, Mark S Neubauer, Avik Roy

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Qualitative and quantitative enhancement of parameter estimation for model-based diagnostics using automatic differentiation with an application to inertial fusion by A L Milder, A S Joglekar, W Rozmus, D H Froula

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Machine-learning accelerated identification of exfoliable two-dimensional materials by Mohammad Tohidi Vahdat, Kumar Varoon Agrawal, Giovanni Pizzi

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Data-driven dynamics reconstruction using RBF network by Cong-Cong Du, Xuan Wang, Zhangsen Wang, Da-Hui Wang

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A method for quantifying the generalization capabilities of generative models for solving Ising models by Qunlong Ma, Zhi Ma, Ming Gao

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Differentiable simulation of a liquid argon time projection chamber by Sean Gasiorowski, Yifan Chen, Youssef Nashed, Pierre Granger, Camelia Mironov, Ka Vang Tsang, Daniel Ratner, Kazuhiro Terao

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Actively learning costly reward functions for reinforcement learning by André Eberhard, Houssam Metni, Georg Fahland, Alexander Stroh, Pascal Friederich

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Towards automatic setup of 18 MeV electron beamline using machine learning by Francesco Maria Velotti, Brennan Goddard, Verena Kain, Rebecca Ramjiawan, Giovanni Zevi Della Porta, Simon Hirlaender

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Optimizing collective behavior of communicating active particles with machine learning by Jens Grauer, Fabian Jan Schwarzendahl, Hartmut Löwen, Benno Liebchen

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Deep learning-based detection and identification of brain tumor biomarkers in quantitative MR-images by Iulian Emil Tampu, Neda Haj-Hosseini, Ida Blystad, Anders Eklund

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