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  • Hybrid machine learning and Gaussian process for antenna parameter estimation

  • Misilmani, H. M. E. & Naous, T. Machine learning in antenna design: An overview on machine learning concept and algorithms. In 2019 International Conference on High Performance Computing & Simulation (HPCS), 600–607 (2019).

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  • Cross-domain continuous-scale remote sensing image super-resolution via meta-weight learning

  • Tang, D. et al. Aerogen: Enhancing remote sensing object detection with diffusion-driven data generation. In 2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 3614–3624, https://doi.org/10.1109/CVPR52734.2025.00342…

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  • A detection of sulfur-bearing cyclic hydrocarbons in space

    A detection of sulfur-bearing cyclic hydrocarbons in space

    Laboratory identification

    The experimental search for 2,5-CT and 2,4-CT was guided by ab initio quantum chemical calculations that derived the main spectroscopic parameters from geometry optimization and harmonic force field analysis (section…

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  • The impact of K selection in K‑fold cross-validation on bias and variance in supervised learning models

  • Mitchell, T. M. & Mitchell, T. M. Machine Learning Vol. 1 (McGraw-Hill, 1997).

  • Saeed, A., Husnain, A., Rasool, S., Gill, A. Y. & Amelia, A. Healthcare revolution: how AI and machine learning are changing medicine. Res. Social Sci. Econ. Manage. 3…

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  • Computation of topological relations with 3-SRM

  • Freeman, J. The modelling of spatial relations. Comput. Graph. Image Process. 4(2), 156–171 (1975).

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  • Hazelton, N. W., Bennett, L. M. & Masel, J. Topological structures for four-dimensional…

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  • Orange-peel-derived carbon dots embedded in polyvinyl alcohol films for transparent and flexible UV-blocking applications

    Orange-peel-derived carbon dots embedded in polyvinyl alcohol films for transparent and flexible UV-blocking applications

  • Hattori H, Ide Y, Sano T. Microporous titanate nanofibers for highly efficient UV-protective transparent coating. J Mater Chem A. 2014;2:16381–8.

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  • Vallejo JJ, Mesa M,…

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  • Simulation-based inference for precision neutrino physics through neural Monte Carlo tuning

    Simulation-based inference for precision neutrino physics through neural Monte Carlo tuning

  • Capozzi, F. et al. Neutrino masses and mixing: entering the era of subpercent precision. Phys. Rev. D. 111, 093006 (2025).

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  • Agostini, M. et al. The Monte Carlo simulation of the Borexino…

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  • Nonequilibrium pulsed heating freezes sintering of supported metal nanocatalysts

  • Muhammad, P. et al. Defect engineering in nanocatalysts: from design and synthesis to applications. Adv. Funct. Mater. 34, 2314686 (2024).

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  • Li, C., Clament Sagaya Selvam, N. & Fang, J….

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  • Text mining-assisted machine learning prediction and experimental validation of emission wavelengths

  • Himanen, L., Geurts, A., Foster, A. S. & Rinke, P. Data-driven materials science: status, challenges, and perspectives. Adv. Sci. 6 https://doi.org/10.1002/advs.201900808 (2019).

  • Pollice, R. et al. Data-driven strategies for accelerated materials…

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