Estimation of vegetation chlorophyll content with Variational Heteroscedastic Gaussian Processes
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[1] George Eastman House,et al. Sparse Bayesian Learning and the Relevance Vector Machine , 2001 .
[2] Luis Gómez-Chova,et al. Biophysical Parameter Estimation With a Semisupervised Support Vector Machine , 2009, IEEE Geoscience and Remote Sensing Letters.
[3] Miguel Lázaro-Gredilla,et al. Variational Heteroscedastic Gaussian Process Regression , 2011, ICML.
[4] Bernhard Schölkopf,et al. A tutorial on support vector regression , 2004, Stat. Comput..
[5] Luis Alonso,et al. Multioutput Support Vector Regression for Remote Sensing Biophysical Parameter Estimation , 2011, IEEE Geoscience and Remote Sensing Letters.
[6] Carl E. Rasmussen,et al. Gaussian processes for machine learning , 2005, Adaptive computation and machine learning.
[7] Gustavo Camps-Valls,et al. Retrieval of oceanic chlorophyll concentration with relevance vector machines , 2006 .
[8] S. Durbha,et al. Support vector machines regression for retrieval of leaf area index from multiangle imaging spectroradiometer , 2007 .
[9] Kristian Kersting,et al. Kernel Conditional Quantile Estimation via Reduction Revisited , 2009, 2009 Ninth IEEE International Conference on Data Mining.
[10] Michael I. Jordan,et al. Regression with input-dependent noise: A Gaussian process treatment , 1998 .
[11] Wolfram Burgard,et al. Most likely heteroscedastic Gaussian process regression , 2007, ICML '07.