0585538 20250526122022.020240429235959.9 10.5194/egusphere-egu24-5960 Estimation of spatio-temporal source of microplastics using Bayesian Neural networks 1 s. E EGU General Assembly 2024Atmospheric microplastics and nanoplasticsMunichThe European Geosciences Union2024 airborne microplastics cav_un_auth*0464277 Brožová Antonie UTIA-B Adaptivní systémy Department of Adaptive Systems AS AS CZ Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0101207 Šmídl Václav UTIA-B Adaptivní systémy Department of Adaptive Systems AS AS Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0267768 Tichý Ondřej UTIA-B Adaptivní systémy Department of Adaptive Systems AS AS Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0363740 Evangeliou N. NO http://library.utia.cas.cz/separaty/2024/AS/brozova-0585538.pdf GA24-10400S GA ČR CZ cav_un_auth*0464279 In this contribution, we solve the same inverse problem as in [1] using a source term estimator in the form of a spatial Bayesian neural network [2]. cav_un_auth*0466707 EGU General Assembly 2024 20240414 20240419 Vienna AT 2025 4 2 O 4 4o 4 20250526122015.0 4 20250526122022.0 PO RVO:67985556 https://hdl.handle.net/11104/0353243 S EGU24-5960 2024 Soubory v repozitáři: 0585538.pdf SCOPUS PUBMED WOS EGU General Assembly 2024 Atmospheric microplastics and nanoplastics Munich The European Geosciences Union 2024