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Reconstruction of Incomplete Wildfire Data using Deep Generative Models

Reconstruction of Incomplete Wildfire Data using Deep Generative Models

16 January 2022
T. Ivek
Domagoj Vlah
    SyDa
ArXivPDFHTML

Papers citing "Reconstruction of Incomplete Wildfire Data using Deep Generative Models"

4 / 4 papers shown
Title
Regression modelling of spatiotemporal extreme U.S. wildfires via
  partially-interpretable neural networks
Regression modelling of spatiotemporal extreme U.S. wildfires via partially-interpretable neural networks
J. Richards
Raphael Huser
28
13
0
16 Aug 2022
Next Day Wildfire Spread: A Machine Learning Data Set to Predict
  Wildfire Spreading from Remote-Sensing Data
Next Day Wildfire Spread: A Machine Learning Data Set to Predict Wildfire Spreading from Remote-Sensing Data
F. Huot
R. Hu
N. Goyal
T. Sankar
M. Ihme
Yi-Fan Chen
61
67
0
04 Dec 2021
A Style-Based Generator Architecture for Generative Adversarial Networks
A Style-Based Generator Architecture for Generative Adversarial Networks
Tero Karras
S. Laine
Timo Aila
312
10,391
0
12 Dec 2018
A disciplined approach to neural network hyper-parameters: Part 1 --
  learning rate, batch size, momentum, and weight decay
A disciplined approach to neural network hyper-parameters: Part 1 -- learning rate, batch size, momentum, and weight decay
L. Smith
208
1,020
0
26 Mar 2018
1