Scaling Up a Metric Learning Algorithm for Image Recognition and Representation. - Adrian Perez-Suay; Francesc J. Ferri (ISVC (2), 2008)

A Random Extension for Discriminative Dimensionality Reduction and Metric Learning. - Adrian Perez-Suay; Francesc J. Ferri; Jesús V. Albert (IbPRIA, 2009)

An Online Metric Learning Approach through Margin Maximization. - Adrian Perez-Suay; Francesc J. Ferri; Jesús V. Albert (IbPRIA, 2011)

Online Metric Learning Methods Using Soft Margins and Least Squares Formulations. - Adrian Perez-Suay; Francesc J. Ferri (SSPR/SPR, 2012)

Comparative Evaluation of Batch and Online Distance Metric Learning Approaches Based on Margin Maximization. - Adrian Perez-Suay; Francesc J. Ferri; Miguel Arevalillo-Herráez; Jesús V. Albert (SMC, 2013)

Passive-aggressive online distance metric learning and extensions. - Adrián Pérez-Suay; Francesc J. Ferri; Miguel Arevalillo-Herráez (Prog. Artif. Intell., 2013)

About Combining Metric Learning and Prototype Generation. - Adrián Pérez-Suay; Francesc J. Ferri; Miguel Arevalillo-Herráez; Jesús V. Albert (S+SSPR, 2014)

Passive millimeter wave image classification with large scale Gaussian processes. - Pablo Morales-Alvarez; Adrian Perez-Suay; Rafael Molina 001; Gustau Camps-Valls; Aggelos K. Katsaggelos (ICIP, 2017)

Efficient remote sensing image classification with Gaussian processes and Fourier features. - Pablo Morales-Alvarez; Adrian Perez-Suay; Rafael Molina 001; Gustau Camps-Valls (IGARSS, 2017)

Causal inference in geosciences with kernel sensitivity maps. - Adrian Perez-Suay; Gustau Camps-Valls (IGARSS, 2017)

Fair Kernel Learning. - Adrián Pérez-Suay; Valero Laparra; Gonzalo Mateo-Garcia; Jordi Muñoz-Marí; Luis Gómez-Chova; Gustau Camps-Valls (ECML/PKDD (1), 2017)

Consistent Regression of Biophysical Parameters with Kernel Methods. - Emiliano Diaz; Adrian Perez-Suay; Valero Laparra; Gustau Camps-Valls (IGARSS, 2018)

Nonlinear Cook Distance for Anomalous Change Detection. - José Antonio Padrón-Hidalgo; Adrian Perez-Suay; Fatih Nar; Gustau Camps-Valls (IGARSS, 2018)

Randomized RX for Target Detection. - Fatih Nar; Adrian Perez-Suay; José Antonio Padrón; Gustau Camps-Valls (IGARSS, 2018)

A Deep Network Approach to Multitemporal Cloud Detection. - Devis Tuia; Benjamin Kellenberger; Adrián Pérez-Suay; Gustau Camps-Valls (IGARSS, 2018)

Sensitivity maps of the Hilbert-Schmidt independence criterion. - Adrián Pérez-Suay; Gustau Camps-Valls (Appl. Soft Comput., 2018)

Warped Gaussian Processes in Remote Sensing Parameter Estimation and Causal Inference. - Anna Mateo-Sanchis; Jordi Muñoz-Marí; Adrian Perez-Suay; Gustau Camps-Valls (IEEE Geosci. Remote. Sens. Lett., 2018)

Pattern Recognition Scheme for Large-Scale Cloud Detection Over Landmarks. - Adrian Perez-Suay; Julia Amorós-López; Luis Gómez-Chova; Jordi Muñoz-Marí; Dieter Just; Gustau Camps-Valls (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2018)

Remote Sensing Image Classification With Large-Scale Gaussian Processes. - Pablo Morales-Alvarez; Adrian Perez-Suay; Rafael Molina 001; Gustau Camps-Valls (IEEE Trans. Geosci. Remote. Sens., 2018)

Convolutional Long Short-Term Memory Network for Multitemporal Cloud Detection Over Landmarks. - Gonzalo Mateo-Garcia; José E. Adsuara; Adrián Pérez-Suay; Luis Gómez-Chova (IGARSS, 2019)

Nonlinear Distribution Regression for Remote Sensing Applications. - José E. Adsuara; Adrián Pérez-Suay; Jordi Muñoz-Marí; Anna Mateo-Sanchis; Maria Piles; Gustau Camps-Valls (IEEE Trans. Geosci. Remote. Sens., 2019)

Causal Inference in Geoscience and Remote Sensing From Observational Data. - Adrian Perez-Suay; Gustau Camps-Valls (IEEE Trans. Geosci. Remote. Sens., 2019)

Discovering Differential Equations from Earth Observation Data. - José E. Adsuara; Adrián Pérez-Suay; Álvaro Moreno-Martínez; Gustau Camps-Valls; Guido Kraemer; Markus Reichstein; Miguel D. Mahecha (IGARSS, 2020)

Down-Scaling Modis Vegetation Products with Landsat GAP Filled Surface Reflectance in Google Earth Engine. - Álvaro Moreno-Martínez; Emma Izquierdo-Verdiguier; Gustau Camps-Valls; Marco P. Maneta; Jordi Muñoz-Marí; Nathaniel P. Robinson; José E. Adsuara; Manuel Campos; F. Javier García-Haro; Adrián Pérez-Suay; Nicholas Clinton; John S. Kimball; et al. (IGARSS, 2020)

Interpretability of Recurrent Neural Networks in Remote Sensing. - Adrián Pérez-Suay; José E. Adsuara; María Piles; Laura Martínez-Ferrer; Emiliano Diaz; Álvaro Moreno-Martínez; Gustau Camps-Valls (IGARSS, 2020)

Kernel Methods and their derivatives: Concept and perspectives for the Earth system sciences. - Juan Emmanuel Johnson; Valero Laparra; Adrián Pérez-Suay; Miguel D. Mahecha; Gustau Camps-Valls (CoRR, 2020)

Living in the Physics and Machine Learning Interplay for Earth Observation. - 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; Luca Martino (CoRR, 2020)

Randomized kernels for large scale Earth observation applications. - Adrián Pérez-Suay; Julia Amorós-López; Luis Gómez-Chova; Valero Laparra; Jordi Muñoz-Marí; Gustau Camps-Valls (CoRR, 2020)

Efficient Kernel Cook's Distance for Remote Sensing Anomalous Change Detection. - José Antonio Padrón-Hidalgo; Adrián Pérez-Suay; Fatih Nar; Valero Laparra; Gustau Camps-Valls (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2020)

Physics-Aware Machine Learning for Geosciences and Remote Sensing. - 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; Luca Martino (IGARSS, 2021)

A Classification of Artificial Intelligence Systems for Mathematics Education. - Steven Van Vaerenbergh; Adrián Pérez-Suay (CoRR, 2021)

Efficient Nonlinear RX Anomaly Detectors. - José Antonio Padrón-Hidalgo; Adrián Pérez-Suay; Fatih Nar; Gustau Camps-Valls (IEEE Geosci. Remote. Sens. Lett., 2021)

Emulation of Synthetic Hyperspectral Sentinel-2-Like Reflectance Images Using Neural Networks. - Miguel Morata; Bastian Siegmann; Adrián Pérez-Suay; Juan Pablo Rivera Caicedo; Jochem Verrelst (IGARSS, 2022)

Kernel dependence regularizers and Gaussian processes with applications to algorithmic fairness. - Zhu Li; Adrián Pérez-Suay; Gustau Camps-Valls; Dino Sejdinovic (Pattern Recognit., 2022)

Introducing ARTMO's Machine-Learning Classification Algorithms Toolbox: Application to Plant-Type Detection in a Semi-Steppe Iranian Landscape. - Masoumeh Aghababaei; Ataollah Ebrahimi; Ali Asghar Naghipour; Esmaeil Asadi; Adrián Pérez-Suay; Miguel Morata; Jose L. Garcia; Juan Pablo Rivera Caicedo; Jochem Verrelst (Remote. Sens., 2022)

Prototyping Crop Traits Retrieval Models for CHIME: Dimensionality Reduction Strategies Applied to PRISMA Data. - Ana Belen Pascual Venteo; Enrique Portales; Katja Berger; Giulia Tagliabue; Jose L. Garcia; Adrián Pérez-Suay; Juan Pablo Rivera Caicedo; Jochem Verrelst (Remote. Sens., 2022)

Interpretable Long Short-Term Memory Networks for Crop Yield Estimation. - Anna Mateo-Sanchis; José E. Adsuara; Maria Piles; Jordi Muñoz-Marí; Adrian Perez-Suay; Gustau Camps-Valls (IEEE Geosci. Remote. Sens. Lett., 2023)

Neural Network Emulation of Synthetic Hyperspectral Sentinel-2-Like Imagery With Uncertainty. - Miguel Morata; Bastian Siegmann; Adrián Pérez-Suay; José Luis García-Soria; Juan Pablo Rivera Caicedo; Jochem Verrelst (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2023)

Fair Kernel Regression through Cross-Covariance Operators. - Adrian Perez-Suay; Paula Gordaliza; Jean-Michel Loubes; Dino Sejdinovic; Gustau Camps-Valls (Trans. Mach. Learn. Res., 2023)

Data-Driven Modeling Through the Moodle Learning Management System: An Empirical Study Based on a Mathematics Teaching Subject. - Adrián Pérez-Suay; Steven Van Vaerenbergh; Pascual D. Diago; Ana Belen Pascual Venteo; Francesc J. Ferri (Rev. Iberoam. de Tecnol. del Aprendiz., 2023)

Assessing the Impact of Using Short Videos for Teaching at Higher Education: Empirical Evidence From Log-Files in a Learning Management System. - Valero Laparra; Adrián Pérez-Suay; María Piles; Jordi Muñoz-Marí; Julia Amorós-López; Roberto Fernandez-Moran; Miguel-Ángel Fernández-Torres; José E. Adsuara (Rev. Iberoam. de Tecnol. del Aprendiz., 2023)

Learning About Student Performance From Moodle Logs in a Higher Education Context With Gaussian Processes. - Adrián Pérez-Suay; Valero Laparra; Steven Van Vaerenbergh; Ana Belen Pascual Venteo (Rev. Iberoam. de Tecnol. del Aprendiz., 2024)

Gaussian Process Regression Hybrid Models for the Top-of-Atmosphere Retrieval of Vegetation Traits Applied to PRISMA and EnMAP Imagery. - Ana Belen Pascual Venteo; Jose L. Garcia; Katja Berger; José Estévez; Jorge Vicent 001; Adrián Pérez-Suay; Shari Van Wittenberghe; Jochem Verrelst (Remote. Sens., 2024)

PLS-based approach for fair representation learning. - Elena M. De-Diego; Adrián Pérez-Suay; Paula Gordaliza; Jean-Michel Loubes (CoRR, 2025)