An information theoretic limit to data amplification by S J Watts, L Crow

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Beware of diffusion models for synthesizing medical images—a comparison with GANs in terms of memorizing brain MRI and chest x-ray images by Muhammad Usman Akbar, Wuhao Wang, Anders Eklund

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ChemLit-QA: a human evaluated dataset for chemistry RAG tasks by Geemi P Wellawatte, Huixuan Guo, Magdalena Lederbauer, Anna Borisova, Matthew Hart, Marta Brucka, Philippe Schwaller

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From STEM-EDXS data to phase separation and quantification using physics-guided NMF by Adrien Teurtrie, Nathanaël Perraudin, Thomas Holvoet, Hui Chen, Duncan T L Alexander, Guillaume Obozinski, Cécile Hébert

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

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Machine learning-based compression of quantum many body physics: PCA and autoencoder representation of the vertex function by Jiawei Zang, Matija Medvidović, Dominik Kiese, Domenico Di Sante, Anirvan M Sengupta, Andrew J Millis

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Process tomography of structured optical gates with convolutional neural networks by Tareq Jaouni, Francesco Di Colandrea, Lorenzo Amato, Filippo Cardano, Ebrahim Karimi

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Dynamic selectout and voting-based federated learning for enhanced medical image analysis by Saeed Iqbal, Adnan N Qureshi, Musaed Alhussein, Khursheed Aurangzeb, Atif Mahmood, Saaidal Razalli Bin Azzuhri

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Neural scaling laws from large-N field theory: solvable model beyond the ridgeless limit by Zhengkang Zhang

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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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Causality-driven feature selection and domain adaptation for enhancing chemical foundation models in downstream tasks by Eduardo Soares, Victor Yukio Shirasuna, Emilio Vital Brazil, Karen Fiorella Aquino Gutierrez, Renato Cerqueira, Dmitry Zubarev, Kristin Schmidt, Daniel P Sanders

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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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Probing the effects of broken symmetries in machine learning by Marcel F Langer, Sergey N Pozdnyakov, Michele Ceriotti

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Efficient prediction of aerodynamic forces in rarefied flow using convolutional neural network based multi-process method by Haifeng Huang, Guobiao Cai, Chuanfeng Wei, Baiyi Zhang, Xiang Cui, Yongjia Zhao, Huiyan Weng, Weizong Wang, Lihui Liu, Bijiao He

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Shallow recurrent decoder for reduced order modeling of E × B plasma dynamics by Farbod Faraji, Maryam Reza, J Nathan Kutz

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Thermal damage detection of EAST internal component based on machine learning by Zhongfang Guan, Bin Zhang, Jian Liu, Jinping Qian, Xianzu Gong, Runze Chen, Zuhao Wang, Binfu Gao, Yutong Guo, Chuannan Xuan, Cong Cao, Tianqi Jia, Pan Li, Wenbin Liu, Wei Wang, Yunchan Hu, Yifan He, Kangjia Yang, Wenyi Lu, Chunyu He, the EAST team

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The more the better or the less the better: LASSO versus random forest in forecasting seasonal precipitation for drought management by Taesam Lee, Yejin Kong, Vijay P Singh

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Quantum generative learning for high-resolution medical image generation by Amena Khatun, Kübra Yeter Aydeniz, Yaakov S Weinstein, Muhammad Usman

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SICGNN: structurally informed convolutional graph neural networks for protein classification by YongHyun Lee, Eunchan Kim, Jiwoong Choi, Changhyun Lee

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Fast jet tagging with MLP-Mixers on FPGAs by Chang Sun, Jennifer Ngadiuba, Maurizio Pierini, Maria Spiropulu

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