Fetching the paper…
Reading the bibliography…
State-of-the-art deep learning methods have shown a remarkable capacity to model complex data domains, but struggle with geospatial data.
Generative Adversarial Networks for Financial Trading Strategies Fine-Tuning and Combination
A. Koshiyama, N. Firoozye, and P. Treleaven · 1901
Earlier work this paper cites.
COCO-GAN: Generation by Parts via Conditional Coordinating
C. H. Lin, C.-C. Chang, Y.-S. Chen, D.-C. Juan, W. Wei, and H.-T. Chen · 1904
Earlier work this paper cites.
Notes on continuous stochastic phenomena
P. A. Moran · 1950
Earlier work this paper cites.
A Computer Movie Simulating Urban Growth in the Detroit Region
W. R. Tobler · 1970
Earlier work this paper cites.
Spatial rainfall estimation by linear and non-linear co-kriging of radar-rainfall and raingage data
A. Azimi-Zonooz, W. F. Krajewski, D. S. Bowles, and D. J. Seo · 1989
Earlier work this paper cites.
Local Indicators of Spatial Association—LISA
L. Anselin · 1995
Earlier work this paper cites.
Analysis of Spatial Autocorrelation in House Prices
S. Basu and T. G. Thibodeau · 1998
Earlier work this paper cites.
The elements of statistical learning , volume 1
J. Friedman, T. Hastie, and R. Tibshirani · 2001
Earlier work this paper cites.
Sparse spatial autoregressions
R. Kelley Pace and R. Barry · 2003
Earlier work this paper cites.
Spatial cross-validation and bootstrap for the assessment of prediction rules in remote sensing: The R package sperrorest
A. Brenning · 2012
Earlier work this paper cites.
Scikit-learn: Machine Learning in Python
F. Pedregosa, G. Varoquaux, A. Gramfort, V. Michel, B. Thirion, O. Grisel, M. Blondel, A. Müller, J. Nothman, G. Louppe, P. Prettenhofer, R. Weiss, V. Dubourg, J. Vanderplas, A. Passos, D. Cournapeau, M. Brucher, M. Perrot, and É. Duchesnay · 2012
Earlier work this paper cites.
Handling Discontinuous Effects in Modeling Spatial Correlation of Wafer-level Analog/RF Tests
K. Huang, N. Kupp, J. M. Carulli, and Y. Makris · 2013
Earlier work this paper cites.
Optimal Spatial Prediction Using Ensemble Machine Learning
M. M. Davies and M. J. Van Der Laan · 2014
Earlier work this paper cites.
Generative Adversarial Nets
I. Goodfellow, J. Pouget-Abadie, M. Mirza, B. Xu, D. Warde-Farley, S. Ozair, A. Courville, and Y. Bengio · 2014
Earlier work this paper cites.
Factorized Point Process Intensities: A Spatial Analysis of Professional Basketball
A. Miller, L. Bornn, R. Adams, and K. Goldsberry · 2014
Earlier work this paper cites.
Conditional generative adversarial networks
M. Mirza and S. Osindero · 2014
Earlier work this paper cites.
Hierarchical Nearest-Neighbor Gaussian Process Models for Large Geostatistical Datasets
A. Datta, S. Banerjee, A. O. Finley, and A. E. Gelfand · 2015
Cited alongside, same era.
Soccer Jersey Number Recognition Using Convolutional Neural Networks
S. Gerke, K. Müller, and R. Schäfer · 2015
Cited alongside, same era.
Deep Convolutional Networks on Graph-Structured Data
M. Henaff, J. Bruna, and Y. LeCun · 2015
Cited alongside, same era.
Bayesian marked point process modeling for generating fully synthetic public use data with point-referenced geography
H. Quick, S. H. Holan, C. K. Wikle, and J. P. Reiter · 2015
Cited alongside, same era.
Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting
X. Shi, Z. Chen, H. Wang, D.-Y. Yeung, W.-k. Wong, and W.-c. Woo · 2015
Cited alongside, same era.
Least squares generative adversarial networks
X. Mao, Q. Li, H. Xie, R. Y. Lau, Z. Wang, and S. P. Smolley · 2017
Later among the works it cites.
Estimating the prediction performance of spatial models via spatial k-fold cross validation
J. Pohjankukka, T. Pahikkala, P. Nevalainen, and J. Heikkonen · 2017
Later among the works it cites.
Wasserstein Learning of Deep Generative Point Process Models
S. Xiao, M. Farajtabar, X. Ye, J. Yan, L. Song, and H. Zha · 2017
Later among the works it cites.
GAN Augmentation: Augmenting Training Data using Generative Adversarial Networks
C. Bowles, L. Chen, R. Guerrero, P. Bentley, R. Gunn, A. Hammers, D. A. Dickie, M. V. Hernández, J. Wardlaw, and D. Rueckert · 2018
Later among the works it cites.
Synthetic data augmentation using GAN for improved liver lesion classification
M. Frid-Adar, E. Klang, M. Amitai, J. Goldberger, and H. Greenspan · 2018
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering
M. Defferrard, X. Bresson, and P. Vandergheynst · 2016
Cited alongside, same era.
Computer age statistical inference , volume 5
B. Efron and T. Hastie · 2016
Cited alongside, same era.
Fast guided global interpolation for depth and motion
Y. Li, D. Min, M. N. Do, and J. Lu · 2016
Cited alongside, same era.
Improved techniques for training gans
T. Salimans, I. Goodfellow, W. Zaremba, V. Cheung, A. Radford, and X. Chen · 2016
Cited alongside, same era.
Wasserstein generative adversarial networks
M. Arjovsky, S. Chintala, and L. Bottou · 2017
Cited alongside, same era.
A Point Set Generation Network for 3D Object Reconstruction From a Single Image
H. Fan, H. Su, and L. J. Guibas · 2017
Cited alongside, same era.
Improved training of wasserstein gans
I. Gulrajani, F. Ahmed, M. Arjovsky, V. Dumoulin, and A. C. Courville · 2017
Cited alongside, same era.
J. R. Gardner, G. Pleiss, D. Bindel, K. Q. Weinberger, and A. G. Wilson · 2018
Later among the works it cites.
C.-L. Li, M. Zaheer, Y. Zhang, B. Poczos, and R. Salakhutdinov · 2018
Later among the works it cites.
Learning long-range spatial dependencies with horizontal gated-recurrent units
D. Linsley, J. Kim, V. Veerabadran, and T. Serre · 2018
Later among the works it cites.
Improving Deep Learning with Generic Data Augmentation
L. Taylor and G. Nitschke · 2018
Later among the works it cites.
A novel ensemble modeling approach for the spatial prediction of tropical forest fire susceptibility using LogitBoost machine learning classifier and multi-source geospatial data
M. S. Tehrany, S. Jones, F. Shabani, F. Martínez-Álvarez, and D. Tien Bui · 2018
Later among the works it cites.
Evolutionary generative adversarial networks
C. Wang, C. Xu, X. Yao, and D. Tao · 2018
Later among the works it cites.
VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection
Y. Zhou and O. Tuzel · 2018
Later among the works it cites.
A Local Indicator of Multivariate Spatial Association: Extending Geary’s c
L. Anselin · 2019
Closest in time.
Tile2Vec: Unsupervised representation learning for spatially distributed data
N. Jean, S. Wang, A. Samar, G. Azzari, D. Lobell, and S. Ermon · 2019
Closest in time.
Deep learning and process understanding for data-driven Earth system science
M. Reichstein, G. Camps-Valls, B. Stevens, M. Jung, J. Denzler, N. Carvalhais, and Prabhat · 2019
Closest in time.
Spatial interpolation using conditional generative adversarial neural networks
D. Zhu, X. Cheng, F. Zhang, X. Yao, Y. Gao, and Y. Liu · 2019
Closest in time.