[1] Steven Van Vaerenbergh and Adrián Pérez-Suay. A classification of artificial intelligence systems for mathematics education. CoRR, abs/2107.06015, 2021. [ bib | arXiv | http ]
[2] José Antonio Padrón-Hidalgo, Adrián Pérez-Suay, Fatih Nar, and Gustau Camps-Valls. Efficient nonlinear RX anomaly detectors. IEEE Geosci. Remote. Sens. Lett., 18(2):231--235, 2021. [ bib | DOI | http ]
[3] Adrián Pérez-Suay and Gustau Camps-Valls. Causal inference in geosciences with kernel sensitivity maps. CoRR, abs/2012.14303, 2020. [ bib | arXiv | http ]
[4] Fatih Nar, Adrián Pérez-Suay, José Antonio Padrón, and Gustau Camps-Valls. Randomized RX for target detection. CoRR, abs/2012.12308, 2020. [ bib | arXiv | http ]
[5] José Antonio Padrón-Hidalgo, Adrián Pérez-Suay, Fatih Nar, and Gustau Camps-Valls. Nonlinear cook distance for anomalous change detection. CoRR, abs/2012.12307, 2020. [ bib | arXiv | http ]
[6] Adrián Pérez-Suay, Julia Amorós-López, Luis Gómez-Chova, Jordi Muñoz-Marí, Dieter Just, and Gustau Camps-Valls. Pattern recognition scheme for large-scale cloud detection over landmarks. CoRR, abs/2012.12306, 2020. [ bib | arXiv | http ]
[7] Anna Mateo-Sanchis, Jordi Muñoz-Marí, Adrián Pérez-Suay, and Gustau Camps-Valls. Warped gaussian processes in remote sensing parameter estimation and causal inference. CoRR, abs/2012.12105, 2020. [ bib | arXiv | http ]
[8] Devis Tuia, Benjamin Kellenberger, Adrián Pérez-Suay, and Gustau Camps-Valls. A deep network approach to multitemporal cloud detection. CoRR, abs/2012.10393, 2020. [ bib | arXiv | http ]
[9] José E. Adsuara, Adrián Pérez-Suay, Jordi Muñoz-Marí, Anna Mateo-Sanchis, Maria Piles, and Gustau Camps-Valls. Nonlinear distribution regression for remote sensing applications. CoRR, abs/2012.06377, 2020. [ bib | arXiv | http ]
[10] José Antonio Padrón-Hidalgo, Adrián Pérez-Suay, Fatih Nar, and Gustau Camps-Valls. Efficient nonlinear RX anomaly detectors. CoRR, abs/2012.05799, 2020. [ bib | arXiv | http ]
[11] Adrián Pérez-Suay and Gustau Camps-Valls. Causal inference in geoscience and remote sensing from observational data. CoRR, abs/2012.05150, 2020. [ bib | arXiv | http ]
[12] Emiliano Diaz, Adrián Pérez-Suay, Valero Laparra, and Gustau Camps-Valls. Consistent regression of biophysical parameters with kernel methods. CoRR, abs/2012.04922, 2020. [ bib | arXiv | http ]
[13] Adrián Pérez-Suay, Julia Amorós-López, Luis Gómez-Chova, Valero Laparra, Jordi Muñoz-Marí, and Gustau Camps-Valls. Randomized kernels for large scale earth observation applications. CoRR, abs/2012.03630, 2020. [ bib | arXiv | http ]
[14] Gustau Camps-Valls, Daniel H. Svendsen, Jordi Cortés-Andrés, Álvaro Moreno-Martínez, Adrián Pérez-Suay, José E. Adsuara, Irene Martín, Maria Piles, Jordi Muñoz-Marí, and Luca Martino. Living in the physics and machine learning interplay for earth observation. CoRR, abs/2010.09031, 2020. [ bib | arXiv | http ]
[15] Juan Emmanuel Johnson, Valero Laparra, Adrián Pérez-Suay, Miguel D. Mahecha, and Gustau Camps-Valls. Kernel methods and their derivatives: Concept and perspectives for the earth system sciences. CoRR, abs/2007.14706, 2020. [ bib | arXiv | http ]
[16] José E. Adsuara, Adrián Pérez-Suay, Álvaro Moreno-Martínez, Gustau Camps-Valls, Guido Kraemer, Markus Reichstein, and Miguel D. Mahecha. Discovering differential equations from earth observation data. In IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2020, Waikoloa, HI, USA, September 26 - October 2, 2020, pages 3999--4002. IEEE, 2020. [ bib | DOI | http ]
[17] Adrián Pérez-Suay, José E. Adsuara, María Piles, Laura Martínez-Ferrer, Emiliano Diaz, Álvaro Moreno-Martínez, and Gustau Camps-Valls. Interpretability of recurrent neural networks in remote sensing. In IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2020, Waikoloa, HI, USA, September 26 - October 2, 2020, pages 3991--3994. IEEE, 2020. [ bib | DOI | http ]
[18] Álvaro Moreno-Martínez, Emma Izquierdo-Verdiguier, Gustau Camps-Valls, Marco Moneta, Jordi Muñoz-Marí, Nathaniel P. Robinson, José E. Adsuara, Manuel Campos, F. Javier García-Haro, Adrián Pérez-Suay, Nicholas Clinton, John S. Kimball, and Steven W. Running. Down-scaling modis vegetation products with landsat GAP filled surface reflectance in google earth engine. In IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2020, Waikoloa, HI, USA, September 26 - October 2, 2020, pages 2320--2323. IEEE, 2020. [ bib | DOI | http ]
[19] José Antonio Padrón-Hidalgo, Adrián Pérez-Suay, Fatih Nar, Valero Laparra, and Gustau Camps-Valls. Efficient kernel cook's distance for remote sensing anomalous change detection. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 13:5480--5488, 2020. [ bib | DOI | http ]
[20] Zhu Li, Adrian Perez-Suay, Gustau Camps-Valls, and Dino Sejdinovic. Kernel dependence regularizers and gaussian processes with applications to algorithmic fairness. CoRR, abs/1911.04322, 2019. [ bib | arXiv | http ]
[21] Gonzalo Mateo-Garcia, José E. Adsuara, Adrián Pérez-Suay, and Luis Gómez-Chova. Convolutional long short-term memory network for multitemporal cloud detection over landmarks. In 2019 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019, Yokohama, Japan, July 28 - August 2, 2019, pages 210--213. IEEE, 2019. [ bib | DOI | http ]
[22] José E. Adsuara, Adrián Pérez-Suay, Jordi Muñoz-Marí, Anna Mateo-Sanchis, Maria Piles, and Gustau Camps-Valls. Nonlinear distribution regression for remote sensing applications. IEEE Trans. Geosci. Remote. Sens., 57(12):10025--10035, 2019. [ bib | DOI | http ]
[23] Adrian Perez-Suay and Gustau Camps-Valls. Causal inference in geoscience and remote sensing from observational data. IEEE Trans. Geosci. Remote. Sens., 57(3):1502--1513, 2019. [ bib | DOI | http ]
[24] José Antonio Padrón-Hidalgo, Adrian Perez-Suay, Fatih Nar, and Gustau Camps-Valls. Nonlinear cook distance for anomalous change detection. In 2018 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018, Valencia, Spain, July 22-27, 2018, pages 5025--5028. IEEE, 2018. [ bib | DOI | http ]
[25] Devis Tuia, Benjamin Kellenberger, Adrián Pérez-Suay, and Gustau Camps-Valls. A deep network approach to multitemporal cloud detection. In 2018 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018, Valencia, Spain, July 22-27, 2018, pages 4351--4354. IEEE, 2018. [ bib | DOI | http ]
[26] Fatih Nar, Adrian Perez-Suay, José Antonio Padrón, and Gustau Camps-Valls. Randomized RX for target detection. In 2018 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018, Valencia, Spain, July 22-27, 2018, pages 4237--4240. IEEE, 2018. [ bib | DOI | http ]
[27] Emiliano Diaz, Adrian Perez-Suay, Valero Laparra, and Gustau Camps-Valls. Consistent regression of biophysical parameters with kernel methods. In 2018 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018, Valencia, Spain, July 22-27, 2018, pages 4047--4050. IEEE, 2018. [ bib | DOI | http ]
[28] Pablo Morales-Alvarez, Adrian Perez-Suay, Rafael Molina, and Gustau Camps-Valls. Remote sensing image classification with large-scale gaussian processes. IEEE Trans. Geosci. Remote. Sens., 56(2):1103--1114, 2018. [ bib | DOI | http ]
[29] Adrian Perez-Suay, Julia Amorós-López, Luis Gómez-Chova, Jordi Muñoz-Marí, Dieter Just, and Gustau Camps-Valls. Pattern recognition scheme for large-scale cloud detection over landmarks. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 11(11):3977--3987, 2018. [ bib | DOI | http ]
[30] Anna Mateo-Sanchis, Jordi Muñoz-Marí, Adrian Perez-Suay, and Gustau Camps-Valls. Warped gaussian processes in remote sensing parameter estimation and causal inference. IEEE Geosci. Remote. Sens. Lett., 15(11):1647--1651, 2018. [ bib | DOI | http ]
[31] Adrián Pérez-Suay and Gustau Camps-Valls. Sensitivity maps of the hilbert-schmidt independence criterion. Appl. Soft Comput., 70:1054--1063, 2018. [ bib | DOI | http ]
[32] Pablo Morales-Alvarez, Adrian Perez-Suay, Rafael Molina, and Gustau Camps-Valls. Remote sensing image classification with large scale gaussian processes. CoRR, abs/1710.00575, 2017. [ bib | arXiv | http ]
[33] Adrián Pérez-Suay, Valero Laparra, Gonzalo Mateo-Garcia, Jordi Muñoz-Marí, Luis Gómez-Chova, and Gustau Camps-Valls. Fair kernel learning. In Michelangelo Ceci, Jaakko Hollmén, Ljupco Todorovski, Celine Vens, and Saso Dzeroski, editors, Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2017, Skopje, Macedonia, September 18-22, 2017, Proceedings, Part I, volume 10534 of Lecture Notes in Computer Science, pages 339--355. Springer, 2017. [ bib | DOI | http ]
[34] Pablo Morales-Alvarez, Adrian Perez-Suay, Rafael Molina, and Gustau Camps-Valls. Efficient remote sensing image classification with gaussian processes and fourier features. In 2017 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2017, Fort Worth, TX, USA, July 23-28, 2017, pages 2227--2230. IEEE, 2017. [ bib | DOI | http ]
[35] Adrian Perez-Suay and Gustau Camps-Valls. Causal inference in geosciences with kernel sensitivity maps. In 2017 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2017, Fort Worth, TX, USA, July 23-28, 2017, pages 763--766. IEEE, 2017. [ bib | DOI | http ]
[36] Pablo Morales-Alvarez, Adrian Perez-Suay, Rafael Molina, Gustau Camps-Valls, and Aggelos K. Katsaggelos. Passive millimeter wave image classification with large scale gaussian processes. In 2017 IEEE International Conference on Image Processing, ICIP 2017, Beijing, China, September 17-20, 2017, pages 370--374. IEEE, 2017. [ bib | DOI | http ]
[37] Adrián Pérez-Suay, Francesc J. Ferri, Miguel Arevalillo-Herráez, and Jesús V. Albert. About combining metric learning and prototype generation. In Pasi Fränti, Gavin Brown, Marco Loog, Francisco Escolano, and Marcello Pelillo, editors, Structural, Syntactic, and Statistical Pattern Recognition - Joint IAPR International Workshop, S+SSPR 2014, Joensuu, Finland, August 20-22, 2014. Proceedings, volume 8621 of Lecture Notes in Computer Science, pages 323--332. Springer, 2014. [ bib | DOI | http ]
[38] Adrian Perez-Suay, Francesc J. Ferri, Miguel Arevalillo-Herráez, and Jesús V. Albert. Comparative evaluation of batch and online distance metric learning approaches based on margin maximization. In IEEE International Conference on Systems, Man, and Cybernetics, Manchester, SMC 2013, United Kingdom, October 13-16, 2013, pages 3511--3515. IEEE, 2013. [ bib | DOI | http ]
[39] Adrián Pérez-Suay, Francesc J. Ferri, and Miguel Arevalillo-Herráez. Passive-aggressive online distance metric learning and extensions. Prog. Artif. Intell., 2(1):85--96, 2013. [ bib | DOI | http ]
[40] Adrian Perez-Suay and Francesc J. Ferri. Online metric learning methods using soft margins and least squares formulations. In Georgy L. Gimel'farb, Edwin R. Hancock, Atsushi Imiya, Arjan Kuijper, Mineichi Kudo, Shinichiro Omachi, Terry Windeatt, and Keiji Yamada, editors, Structural, Syntactic, and Statistical Pattern Recognition - Joint IAPR International Workshop, SSPR&SPR 2012, Hiroshima, Japan, November 7-9, 2012. Proceedings, volume 7626 of Lecture Notes in Computer Science, pages 373--381. Springer, 2012. [ bib | DOI | http ]
[41] Adrian Perez-Suay, Francesc J. Ferri, and Jesús V. Albert. An online metric learning approach through margin maximization. In Jordi Vitrià, João Miguel Raposo Sanches, and Mario Hernández, editors, Pattern Recognition and Image Analysis - 5th Iberian Conference, IbPRIA 2011, Las Palmas de Gran Canaria, Spain, June 8-10, 2011. Proceedings, volume 6669 of Lecture Notes in Computer Science, pages 500--507. Springer, 2011. [ bib | DOI | http ]
[42] Adrian Perez-Suay, Francesc J. Ferri, and Jesús V. Albert. A random extension for discriminative dimensionality reduction and metric learning. In Helder Araújo, Ana Maria Mendonça, Armando J. Pinho, and M. Inés Torres, editors, Pattern Recognition and Image Analysis, 4th Iberian Conference, IbPRIA 2009, Póvoa de Varzim, Portugal, June 10-12, 2009, Proceedings, volume 5524 of Lecture Notes in Computer Science, pages 370--377. Springer, 2009. [ bib | DOI | http ]
[43] Adrian Perez-Suay and Francesc J. Ferri. Scaling up a metric learning algorithm for image recognition and representation. In George Bebis, Richard D. Boyle, Bahram Parvin, Darko Koracin, Paolo Remagnino, Fatih Murat Porikli, Jörg Peters, James T. Klosowski, Laura L. Arns, Yu Ka Chun, Theresa-Marie Rhyne, and Laura Monroe, editors, Advances in Visual Computing, 4th International Symposium, ISVC 2008, Las Vegas, NV, USA, December 1-3, 2008. Proceedings, Part II, volume 5359 of Lecture Notes in Computer Science, pages 592--601. Springer, 2008. [ bib | DOI | http ]

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