PHYSICS-INFORMED NEURAL NETWORKS FOR INVERSE TASKS OF ONE-DIMENSIONAL WAVE PROPAGATION
Електроніка та інформаційні технологіїBackground. Physics‑informed neural networks (PINNs) are a family of learning methods that guide neural networks with the laws of physics, rather than relying only on data.
Igor Kolych, Roman Shuvar
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The Impact of Cloud Computing on Geophysical and Seismological Research
Cloud computing is transforming the landscape of geophysical and seismological research by providing scalable, cost-effective, and flexible solutions for data storage, processing, and collaboration. This article explores the key cloud service models—Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS)—and ...
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SLR-Net: Lightweight and Accurate Detection of Weak Small Objects in Satellite Laser Ranging Imagery. [PDF]
Sensors (Basel)Zhu W, Hu J, Gong W, Wang Y, Zhang Y.
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Passive seismological approaches for localizing near-surface fiber-optic cables with DAS. [PDF]
Sci RepRümpker G, Limberger F, Komeazi A.
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GMF-Net: A Gaussian-Matched Fusion Network for Weak Small Object Detection in Satellite Laser Ranging Imagery. [PDF]
Sensors (Basel)Zhu W, Gong W, Wang Y, Zhang Y, Hu J.
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Insights into the seismogenesis and tectonic implications of an isolated intraplate earthquake (M4.0) on February 17, 2025, in Delhi. [PDF]
Sci RepPrajapati SK +4 more
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Near-surface geophysics: from measurements to reliable models. [PDF]
Sci RepMaciuk K, Biswas A, Kumar S, Rai AK.
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Viscous and thermal effects on wave propagation in a micropolar viscothermoelastic medium with impedance considerations. [PDF]
Sci RepAdel M +5 more
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Learning earthquake ground motions via conditional generative modeling. [PDF]
Nat CommunRen P +11 more
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