High-dimensional reinforcement learning for optimization and control of ultracold quantum gases by N Milson, A Tashchilina, T Ooi, A Czarnecka, Z F Ahmad, L J LeBlanc

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Neural-prior stochastic block model by O Duranthon, L Zdeborová

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Fast regression of the tritium breeding ratio in fusion reactors by P Mánek, G Van Goffrier, V Gopakumar, N Nikolaou, J Shimwell, I Waldmann

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Prediction of 4D stress field evolution around additive manufacturing-induced porosity through progressive deep-learning frameworks by Mohammad Rezasefat, James D Hogan

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Probability flow solution of the Fokker–Planck equation by Nicholas M Boffi, Eric Vanden-Eijnden

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CoRe optimizer: an all-in-one solution for machine learning by Marco Eckhoff, Markus Reiher

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Rediscovering orbital mechanics with machine learning by Pablo Lemos, Niall Jeffrey, Miles Cranmer, Shirley Ho, Peter Battaglia

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A robust estimator of mutual information for deep learning interpretability by Davide Piras, Hiranya V Peiris, Andrew Pontzen, Luisa Lucie-Smith, Ningyuan Guo, Brian Nord

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Artificial neural network potentials for mechanics and fracture dynamics of two-dimensional crystals by Gang Seob Jung, Hunjoo Myung, Stephan Irle

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Discovering interpretable physical models using symbolic regression and discrete exterior calculus by Simone Manti, Alessandro Lucantonio

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Categorical representation learning and RG flow operators for algorithmic classifiers by Artan Sheshmani, Yi-Zhuang You, Wenbo Fu, Ahmadreza Azizi

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Restricted Boltzmann machine representation for the groundstate and excited states of Kitaev Honeycomb model by Mohammadreza Noormandipour, Sun Youran, Babak Haghighat

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Interpretable machine learning model to predict survival days of malignant brain tumor patients by Snehal Rajput, Rupal A Kapdi, Mehul S Raval, Mohendra Roy

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A finite element-convolutional neural network model (FE-CNN) for stress field analysis around arbitrary inclusions by Mohammad Rezasefat, James D Hogan

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Mapping confinement potentials and charge densities of interacting quantum systems using conditional generative adversarial networks by Calin-Andrei Pantis-Simut, Amanda Teodora Preda, Lucian Ion, Andrei Manolescu, George Alexandru Nemnes

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Koopman-inspired approach for identification of exogenous anomalies in nonstationary time-series data by Alex Mallen, Christoph A Keller, J Nathan Kutz

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Improving SOH estimation for lithium-ion batteries using TimeGAN by Sujin Seol, Jungeun Lee, Jaewoo Yoon, Byeongwoo Kim

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Deep learning of crystalline defects from TEM images: a solution for the problem of ‘never enough training data’ by Kishan Govind, Daniela Oliveros, Antonin Dlouhy, Marc Legros, Stefan Sandfeld

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Spectral density classification for environment spectroscopy by J Barr, G Zicari, A Ferraro, M Paternostro

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WATUNet: a deep neural network for segmentation of volumetric sweep imaging ultrasound by Donya Khaledyan, Thomas J Marini, Avice O’Connell, Steven Meng, Jonah Kan, Galen Brennan, Yu Zhao, Timothy M Baran, Kevin J Parker

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