Search Results - "Machine Learning: Science and Technology"

An informativeness score for optimal mixed datasets using Gaussian process regression by Cameron J LaMack, Eric M Schearer

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Machine learning-guided construction of an analytic kinetic energy functional for orbital free density functional theory by Sergei Manzhos, Johann Lüder, Pavlo Golub, Manabu Ihara

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Sequential learning on a tensor network Born machine with trainable token embedding by Wanda Hou, Miao Li, Yi-Zhuang You

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Stereological 3D modeling of nano-scale catalyst particles using TEM projections by Lukas Fuchs, Kerstin Wein, Jens Friedland, Orkun Furat, Robert Güttel, Volker Schmidt

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Machine-learning based high-bandwidth magnetic sensing by Galya Haim, Stefano Martina, John Howell, Nir Bar-Gill, Filippo Caruso

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Efficient solving of Schrödinger equation using deep convolutional neural network model with an attention mechanism and transfer learning by Ziyi Zhao, Shishun Zhao, Mingjun Zhou, Yujun Yang

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Evidential deep learning for uncertainty quantification and out-of-distribution detection in jet identification using deep neural networks by Ayush Khot, Xiwei Wang, Avik Roy, Volodymyr Kindratenko, Mark S Neubauer

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Randomized tensor network reservoir computing: validity and learnability phase transitions by Shinji Sato, Daiki Sasaki, Chih-Chieh Chen, Kodai Shiba, Tomah Sogabe

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Is tokenization needed for masked particle modeling? by Matthew Leigh, Samuel Klein, François Charton, Tobias Golling, Lukas Heinrich, Michael Kagan, Inês Ochoa, Margarita Osadchy

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Architecture-aware minimization (A2M): how to find flat minima in neural architecture search by Matteo Gambella, Fabrizio Pittorino, Manuel Roveri

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Multi-objective Bayesian optimization of eco-friendly gas mixtures for resistive plate chambers by Pit Bechtold, Dario Stocco, Christian M Franck

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Atomic orbits in molecules and materials for improving machine learning force fields by Anton Charkin-Gorbulin, Artem Kokorin, Huziel E Sauceda, Stefan Chmiela, Claudio Quarti, David Beljonne, Alexandre Tkatchenko, Igor Poltavsky

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Active delta-learning for fast construction of interatomic potentials and stable molecular dynamics simulations by Yaohuang Huang, Yi-Fan Hou, Pavlo O Dral

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Universal machine learning interatomic potentials poised to supplant DFT in modeling general defects in metals and random alloys by Fei Shuang, Zixiong Wei, Kai Liu, Wei Gao, Poulumi Dey

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A neural network approach for line detection in complex atomic emission spectra measured by high-resolution Fourier transform spectroscopy by Milan Ding, Sean Z J Lim, Xiaoran Yu, Christian P Clear, Juliet C Pickering

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Designing precise dynamical steady states in disordered networks by Marc Berneman, Daniel Hexner

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Interpretable classification of Levantine ceramic thin sections via neural networks by Sara Capriotti, Alessio Devoto, Simone Scardapane, Silvano Mignardi, Laura Medeghini

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NeuralPDR: neural differential equations as surrogate models for photodissociation regions by Gijs Vermariën, Thomas G Bisbas, Serena Viti, Yue Zhao, Xuefei Tang, Rahul Ravichandran

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Domain-specific large language model for predicting band gap and formation energy of III-VIIIB and III-IVA nitrides based on fine-tuned GPT-3.5-turbo by Lin Hu, Guozhu Jia

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Bayesian model parameter learning in linear inverse problems: application in EEG focal source imaging by Alexandra Koulouri, Ville Rimpiläinen

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