Improving detection of Parkinson’s disease with acoustic feature optimization using particle swarm optimization and machine learning by Elmoundher Hadjaidji, Mohamed Cherif Amara Korba, Khaled Khelil

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Quantitative assessment of PINN inference on experimental data for gravity currents flows by Mickaël Delcey, Yoann Cheny, Jean Schneider, Simon Becker, Sébastien Kiesgen De Richter

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Machine-learning emergent spacetime from linear response in future tabletop quantum gravity experiments by Koji Hashimoto, Koshiro Matsuo, Masaki Murata, Gakuto Ogiwara, Daichi Takeda

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Machine learning configuration-dependent friction tensors in Langevin heatbaths by Matthias Sachs, Wojciech G Stark, Reinhard J Maurer, Christoph Ortner

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Into the latent space of capacitive sensors: interpolation and synthetic data generation using variational autoencoders by Miguel Monteagudo Honrubia, Francisco Javier Herraiz-Martínez, Javier Matanza Domingo

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Deep unsupervised clustering for prostate auto-segmentation with and without hydrogel spacer by Hengrui Zhao, Biling Wang, Michael Dohopolski, Ti Bai, Steve Jiang, Dan Nguyen

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Deep(er) reconstruction of imaging Cherenkov detectors with swin transformers and normalizing flow models by C Fanelli, J Giroux, J Stevens

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Deep-learning-based canopy height model generation from sub-meter resolution panchromatic satellite imagery by Charles J Abolt, Javier E Santos, Adam L Atchley, Lucas Wells, Daithi Martin, Russell A Parsons, Rodman R Linn

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