103 citations · 199 across the 38 of their papers we have counts for
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cs.LG2023★ 4 cited
Challenges in data-based geospatial modeling for environmental research and practice
Diana Koldasbayeva, Polina Tregubova, Mikhail Gasanov +3
With the rise of electronic data, particularly Earth observation data, data-based geospatial modelling using machine learning (ML) has gained popularity in environmental research.…
physics.geo-ph2023★ 2 cited
Assessing the Risk of Permafrost Degradation with Physics-Informed Machine Learning
Polina Pilyugina, Timofey Chernikov, Alexey Zaytsev +6
Global warming accelerates permafrost degradation, impacting the reliability of critical infrastructure used by more than five million people daily. Furthermore, permafrost thaw pr…