32 citations · 60 across the 4 of their papers we have counts for
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physics.geo-ph2022★ 1 cited
Quantitative analysis of dynamic CT imaging of methane-hydrate formation with a hybrid machine learning approach
Mikhail I. Fokin, Viktor V. Nikitin, Anton A. Duchkov
Fast multi-phase processes in methane hydrate-bearing samples are challenging for micro-CT quantitative study because of complex tomographic data analysis involving time-consuming…
physics.geo-ph2022★ 32 cited
Neural Eikonal Solver: improving accuracy of physics-informed neural networks for solving eikonal equation in case of caustics
Serafim Grubas, Anton Duchkov, Georgy Loginov
The concept of physics-informed neural networks has become a useful tool for solving differential equations due to its flexibility. There are a few approaches using this concept to…