Disentangling Derivatives, Uncertainty and Error in Gaussian Process Models. - Juan Emmanuel Johnson; Valero Laparra; Gustau Camps-Valls (IGARSS, 2018)

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)

Information Theory Measures via Multidimensional Gaussianization. - Valero Laparra; Juan Emmanuel Johnson; Gustau Camps-Valls; Raúl Santos-Rodríguez; Jesus Malo (CoRR, 2020)

Information Theory in Density Destructors. - Juan Emmanuel Johnson; Valero Laparra; Gustau Camps-Valls; Raúl Santos-Rodríguez; Jesús Malo (CoRR, 2020)

RotNet: Fast and Scalable Estimation of Stellar Rotation Periods Using Convolutional Neural Networks. - Juan Emmanuel Johnson; Sairam Sundaresan; Tansu Daylan; Lisseth Gavilan; Daniel K. Giles; Stela Ishitani Silva; Anna Jungbluth; Brett M. Morris; Andrés Muñoz-Jaramillo (CoRR, 2020)

Accounting for Input Noise in Gaussian Process Parameter Retrieval. - Juan Emmanuel Johnson; Valero Laparra; Gustau Camps-Valls (IEEE Geosci. Remote. Sens. Lett., 2020)

Orthonormal Convolutions for the Rotation Based Iterative Gaussianization. - Valero Laparra; Alexander Hepburn; Juan Emmanuel Johnson; Jesús Malo (ICIP, 2022)

The Kernelized Taylor Diagram. - Kristoffer Wickstrøm; Juan Emmanuel Johnson; Sigurd Løkse; Gustau Camps-Valls; Karl Øyvind Mikalsen; Michael Kampffmeyer; Robert Jenssen (NAIS, 2022)

Learning Relevant Features of Optical Water Types. - Katalin Blix; Ana Belen Ruescas; Juan Emmanuel Johnson; Gustau Camps-Valls (IEEE Geosci. Remote. Sens. Lett., 2022)

Learning latent functions for causal discovery. - Emiliano Diaz; Gherardo Varando; Juan Emmanuel Johnson; Gustau Camps-Valls (Mach. Learn. Sci. Technol., 2023)

Estimating Information Theoretic Measures via Multidimensional Gaussianization. - Valero Laparra; Juan Emmanuel Johnson; Gustau Camps-Valls; Raúl Santos-Rodríguez; Jesús Malo (IEEE Trans. Pattern Anal. Mach. Intell., 2025)