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Pregled bibliografske jedinice broj: 1181752

BlackBox: A probabilistic deep learning model for predicting missing spatio-temporal data

Ivek, Tomislav; Vlah, Domagoj
BlackBox: A probabilistic deep learning model for predicting missing spatio-temporal data // Extreme Value Analysis 2021
Edinburgh, Ujedinjeno Kraljevstvo, 2021. (pozvano predavanje, nije recenziran, neobjavljeni rad, znanstveni)

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Naslov
BlackBox: A probabilistic deep learning model for predicting missing spatio-temporal data

Autori
Ivek, Tomislav ; Vlah, Domagoj

Vrsta, podvrsta i kategorija rada
Sažeci sa skupova, neobjavljeni rad, znanstveni

Skup
Extreme Value Analysis 2021

Mjesto i datum
Edinburgh, Ujedinjeno Kraljevstvo, 28.06.2021. - 02.07.2021

Vrsta sudjelovanja
Pozvano predavanje

Vrsta recenzije
Nije recenziran

Ključne riječi
Data reconstruction ; Variational autoencoder ; Convolutional neural network ; Deep learning ; Ensemble ; Extreme Value Analysis Conference challenge ; Wildfires

Sažetak
We present our winning solution model developed for the recent Data Challenge at the Extreme Value Analysis 2021 conference. The Data Challenge was about predicting deliberately missing parts of spatio-temporal numerical data on historical occurrences of wildfires in the United States. Our approach was developed with only a minimal set of assumptions and no specialist knowledge from the field of extreme value analysis.

Izvorni jezik
Engleski

Znanstvena područja
Matematika, Računarstvo



POVEZANOST RADA

Ustanove:
Institut za fiziku, Zagreb,
Fakultet elektrotehnike i računarstva, Zagreb

Profili:

Avatar Url Domagoj Vlah (autor)

Avatar Url Tomislav Ivek (autor)

Citiraj ovu publikaciju:

Ivek, Tomislav; Vlah, Domagoj
BlackBox: A probabilistic deep learning model for predicting missing spatio-temporal data // Extreme Value Analysis 2021
Edinburgh, Ujedinjeno Kraljevstvo, 2021. (pozvano predavanje, nije recenziran, neobjavljeni rad, znanstveni)
Ivek, T. & Vlah, D. (2021) BlackBox: A probabilistic deep learning model for predicting missing spatio-temporal data. U: Extreme Value Analysis 2021.
@article{article, author = {Ivek, Tomislav and Vlah, Domagoj}, year = {2021}, keywords = {Data reconstruction, Variational autoencoder, Convolutional neural network, Deep learning, Ensemble, Extreme Value Analysis Conference challenge, Wildfires}, title = {BlackBox: A probabilistic deep learning model for predicting missing spatio-temporal data}, keyword = {Data reconstruction, Variational autoencoder, Convolutional neural network, Deep learning, Ensemble, Extreme Value Analysis Conference challenge, Wildfires}, publisherplace = {Edinburgh, Ujedinjeno Kraljevstvo} }
@article{article, author = {Ivek, Tomislav and Vlah, Domagoj}, year = {2021}, keywords = {Data reconstruction, Variational autoencoder, Convolutional neural network, Deep learning, Ensemble, Extreme Value Analysis Conference challenge, Wildfires}, title = {BlackBox: A probabilistic deep learning model for predicting missing spatio-temporal data}, keyword = {Data reconstruction, Variational autoencoder, Convolutional neural network, Deep learning, Ensemble, Extreme Value Analysis Conference challenge, Wildfires}, publisherplace = {Edinburgh, Ujedinjeno Kraljevstvo} }

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