An empirical evaluation of generic convolutional and recurrent networks for sequence modeling, 2018. ,
Deep learning for physical processes: Incorporating prior scientific knowledge, 2017. ,
URL : https://hal.archives-ouvertes.fr/hal-02418362
The era-interim reanalysis: Configuration and performance of the data assimilation system, Quarterly Journal of the royal meteorological society, vol.137, pp.553-597, 2011. ,
, , 2005.
, Further improvements to the statistical hurricane intensity prediction scheme (ships), vol.20, pp.531-543
Tropical cyclones. Annual review of earth and planetary sciences 31, pp.75-104, 2003. ,
URL : https://hal.archives-ouvertes.fr/hal-01328819
A nowcasting model for the prediction of typhoon tracks based on a long short term memory neural network, Acta Oceanologica Sinica, vol.37, pp.8-12, 2018. ,
The 2018 climate informatics hackathon: Hurricane intensity forecast, 8th International Workshop on Climate Informatics, 2018. ,
URL : https://hal.archives-ouvertes.fr/hal-01924336
, , 2018.
, Fused deep learning for hurricane track forecast from reanalysis data, Climate Informatics Workshop Proceedings, 2018.
Tropical cyclone track forecasting using fused deep learning from aligned reanalysis data, 2019. ,
URL : https://hal.archives-ouvertes.fr/hal-02329437
How well are tropical cyclones represented in reanalysis datasets, Journal of Climate, vol.30, pp.5243-5264, 2017. ,
, , 2019.
, Deep-hurricane-tracker: Tracking and forecasting extreme climate events, 2019 IEEE Winter Conference on Applications of Computer Vision (WACV) (IEEE), pp.1761-1769
The international best track archive for climate stewardship (ibtracs) unifying tropical cyclone data, Bulletin of the American Meteorological Society, vol.91, pp.363-376, 2010. ,
, One weird trick for parallelizing convolutional neural networks, 2014.
Imagenet classification with deep convolutional neural networks, Advances in neural information processing systems, pp.1097-1105, 2012. ,
How the ncep tropical cyclone tracker works, Preprints, 25th Conf. on Hurricanes and Tropical Meteorology, vol.1, 2002. ,
V-net: Fully convolutional neural networks for volumetric medical image segmentation, 2016 Fourth International Conference on 3D Vision, pp.565-571, 2016. ,
A sparse recurrent neural network for trajectory prediction of atlantic hurricanes, 2016. ,
, Proceedings of the Genetic and Evolutionary Computation Conference, pp.957-964, 2016.
Segmenting and tracking extreme climate events using neural networks, Deep Learning for Physical Sciences (DLPS) Workshop, held with NIPS Conference, 2017. ,
Extremeweather: A large-scale climate dataset for semi-supervised detection, localization, and understanding of extreme weather events, Advances in Neural Information Processing Systems, pp.3402-3413, 2017. ,
Prediction of typhoon tracks using a generative adversarial network with observational and meteorological data, 2018. ,
, , 2015.
, Convolutional lstm network: A machine learning approach for precipitation nowcasting, Advances in neural information processing systems, pp.802-810
Very deep convolutional networks for large-scale image recognition, 2014. ,