Fetching the paper…
Reading the bibliography…
The goal of precipitation nowcasting is to predict the future rainfall intensity in a local region over a relatively short period of time.
The stormy weather group (Canada)
R. H. Douglas · 1990
Earlier work this paper cites.
Long short-term memory
S. Hochreiter and J. Schmidhuber · 1997
Earlier work this paper cites.
SWIRLS-An Evolving Nowcasting System
P.W. Li, W.K. Wong, K.Y. Chan, and E. S.T. Lai · 2000
Earlier work this paper cites.
Scale-dependence of the predictability of precipitation from continental radar images. Part I: Description of the methodology
Urs Germann and Isztar Zawadzki · 2002
Earlier work this paper cites.
High accuracy optical flow estimation based on a theory for warping
T. Brox, A. Bruhn, N. Papenberg, and J. Weickert · 2004
Earlier work this paper cites.
Fluid Simulation for Computer Graphics
R. Bridson · 2008
Earlier work this paper cites.
Quantitative Precipitation Forecasts Based on Radar Observations: Principles, Algorithms and Operational Systems
M. Reyniers · 2008
Earlier work this paper cites.
Theano: a CPU and GPU math expression compiler
J. Bergstra, O. Breuleux, F. Bastien, P. Lamblin, R. Pascanu, G. Desjardins, J. Turian, D. Warde-Farley, and Y. Bengio · 2010
Earlier work this paper cites.
Theano: New features and speed improvements
F. Bastien, P. Lamblin, R. Pascanu, J. Bergstra, I. Goodfellow, A. Bergeron, N. Bouchard, D. Warde-Farley, and Y. Bengio · 2012
Earlier work this paper cites.
Application of optical-flow technique to significant convection nowcast for terminal areas in Hong Kong
P. Cheung and H.Y. Yeung · 2012
Cited alongside, same era.
Lecture 6.5 - RMSProp: Divide the gradient by a running average of its recent magnitude
T. Tieleman and G. Hinton · 2012
Cited alongside, same era.
Generating sequences with recurrent neural networks
A. Graves · 2013
Cited alongside, same era.
On the difficulty of training recurrent neural networks
R. Pascanu, T. Mikolov, and Y. Bengio · 2013
Cited alongside, same era.
Spatio-temporal image pattern prediction method based on a physical model with time-varying optical flow
H. Sakaino · 2013
Cited alongside, same era.
Application of optical flow techniques to rainfall nowcasting
W.C. Woo and W.K. Wong · 2014
Later among the works it cites.
Deep Learning
Y. Bengio, I. Goodfellow, and A. Courville · 2015
Closest in time.
Long-term recurrent convolutional networks for visual recognition and description
J. Donahue, L. A. Hendricks, S. Guadarrama, M. Rohrbach, S. Venugopalan, K. Saenko, and T. Darrell · 2015
Closest in time.
Deep visual-semantic alignments for generating image descriptions
A. Karpathy and L. Fei-Fei · 2015
Closest in time.
A dynamic convolutional layer for short range weather prediction
B. Klein, L. Wolf, and Y. Afek · 2015
Closest in time.
Fully convolutional networks for semantic segmentation
J. Long, E. Shelhamer, and T. Darrell · 2015
Closest in time.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
K. Cho, B. van Merrienboer, C. Gulcehre, F. Bougares, H. Schwenk, and Y. Bengio · 2014
Cited alongside, same era.
Video (language) modeling: a baseline for generative models of natural videos
M. Ranzato, A. Szlam, J. Bruna, M. Mathieu, R. Collobert, and S. Chopra · 2014
Cited alongside, same era.
Use of NWP for nowcasting convective precipitation: Recent progress and challenges
J. Sun, M. Xue, J. W. Wilson, I. Zawadzki, S. P. Ballard, J. Onvlee-Hooimeyer, P. Joe, D. M. Barker, P. W. Li, B. Golding, M. Xu, and J. Pinto · 2014
Cited alongside, same era.
Sequence to sequence learning with neural networks
I. Sutskever, O. Vinyals, and Q. V. Le · 2014
Cited alongside, same era.
Unsupervised learning of video representations using lstms
N. Srivastava, E. Mansimov, and R. Salakhutdinov · 2015
Closest in time.
Show, attend and tell: Neural image caption generation with visual attention
K. Xu, J. Ba, R. Kiros, A. Courville, R. Salakhutdinov, R. Zemel, and Y. Bengio · 2015
Closest in time.