Valero Laparra

Orcid: 0000-0001-7531-9890

According to our database1, Valero Laparra authored at least 73 papers between 2008 and 2023.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2023
A Scalable Reduced-Complexity Compression of Hyperspectral Remote Sensing Images Using Deep Learning.
Remote. Sens., September, 2023

Neural networks with divisive normalization for image segmentation.
Pattern Recognit. Lett., September, 2023

Assessing the Impact of Using Short Videos for Teaching at Higher Education: Empirical Evidence From Log-Files in a Learning Management System.
Rev. Iberoam. de Tecnol. del Aprendiz., August, 2023

Inference over radiative transfer models using variational and expectation maximization methods.
Mach. Learn., March, 2023

Data is Overrated: Perceptual Metrics Can Lead Learning in the Absence of Training Data.
CoRR, 2023

What You Hear Is What You See: Audio Quality Metrics From Image Quality Metrics.
CoRR, 2023

Disentangling the Link Between Image Statistics and Human Perception.
CoRR, 2023

Analysis of Deep Image Quality Models.
CoRR, 2023

2022
Unsupervised Anomaly and Change Detection With Multivariate Gaussianization.
IEEE Trans. Geosci. Remote. Sens., 2022

Retrieval of Physical Parameters With Deep Structured Kernel Regression.
IEEE Trans. Geosci. Remote. Sens., 2022

Neural Networks with Divisive normalization for image segmentation with application in cityscapes dataset.
CoRR, 2022

On the relation between statistical learning and perceptual distances.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Orthonormal Convolutions for the Rotation Based Iterative Gaussianization.
Proceedings of the 2022 IEEE International Conference on Image Processing, 2022

Synthetic Generation of Cardiac MR Images Combining Convolutional Variational Autoencoders and Style Transfer.
Proceedings of the 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2022

Hyperspectral remote sensing data compression with neural networks.
Proceedings of the Data Compression Conference, 2022

2021
Cross-Sensor Adversarial Domain Adaptation of Landsat-8 and Proba-V Images for Cloud Detection.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2021

2020
Efficient Kernel Cook's Distance for Remote Sensing Anomalous Change Detection.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2020

Accounting for Input Noise in Gaussian Process Parameter Retrieval.
IEEE Geosci. Remote. Sens. Lett., 2020

Randomized kernels for large scale Earth observation applications.
CoRR, 2020

Information Theory in Density Destructors.
CoRR, 2020

Information Theory Measures via Multidimensional Gaussianization.
CoRR, 2020

Kernel Methods and their derivatives: Concept and perspectives for the Earth system sciences.
CoRR, 2020

Enforcing perceptual consistency on Generative Adversarial Networks by using the Normalised Laplacian Pyramid Distance.
Proceedings of the 2020 Northern Lights Deep Learning Workshop, 2020

Perceptnet: A Human Visual System Inspired Neural Network For Estimating Perceptual Distance.
Proceedings of the IEEE International Conference on Image Processing, 2020

2019
Kernel Anomalous Change Detection for Remote Sensing Imagery.
IEEE Trans. Geosci. Remote. Sens., 2019

Improved Statistically Based Retrievals via Spatial-Spectral Data Compression for IASI Data.
IEEE Trans. Geosci. Remote. Sens., 2019

Domain Adaptation of Landsat-8 and Proba-V Data Using Generative Adversarial Networks for Cloud Detection.
Proceedings of the 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019

2018
Physics-aware Gaussian processes in remote sensing.
Appl. Soft Comput., 2018

Optimizing Kernel Ridge Regression for Remote Sensing Problems.
Proceedings of the 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018

Transfer Learning with Convolutional Networks for Atmospheric Parameter Retrieval.
Proceedings of the 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018

Disentangling Derivatives, Uncertainty and Error in Gaussian Process Models.
Proceedings of the 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018

Generation of Global Vegetation Products from Eumetsat AVHRR/METOP Satellites.
Proceedings of the 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018

Consistent Regression of Biophysical Parameters with Kernel Methods.
Proceedings of the 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018

2017
Optimized Kernel Entropy Components.
IEEE Trans. Neural Networks Learn. Syst., 2017

Statistical Atmospheric Parameter Retrieval Largely Benefits From Spatial-Spectral Image Compression.
IEEE Trans. Geosci. Remote. Sens., 2017

Perceptually Optimized Image Rendering.
CoRR, 2017

Physics-Aware Gaussian Processes for Earth Observation.
Proceedings of the Image Analysis - 20th Scandinavian Conference, 2017

Fair Kernel Learning.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2017

Eigen-Distortions of Hierarchical Representations.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Spatial noise-aware temperature retrieval from infrared sounder data.
Proceedings of the 2017 IEEE International Geoscience and Remote Sensing Symposium, 2017

Nonlinear statistical retrieval of surface emissivity from IASI data.
Proceedings of the 2017 IEEE International Geoscience and Remote Sensing Symposium, 2017

End-to-end Optimized Image Compression.
Proceedings of the 5th International Conference on Learning Representations, 2017

Probabilistic cross-validation estimators for Gaussian process regression.
Proceedings of the 25th European Signal Processing Conference, 2017

2016
Regression Wavelet Analysis for Lossless Coding of Remote-Sensing Data.
IEEE Trans. Geosci. Remote. Sens., 2016

Sequential Principal Curves Analysis.
CoRR, 2016

Image Denoising with Kernels based on Natural Image Relations.
CoRR, 2016

Density Modeling of Images using a Generalized Normalization Transformation.
Proceedings of the 4th International Conference on Learning Representations, 2016

End-to-end optimization of nonlinear transform codes for perceptual quality.
Proceedings of the 2016 Picture Coding Symposium, 2016

Perceptual image quality assessment using a normalized Laplacian pyramid.
Proceedings of the Human Vision and Electronic Imaging, 2016

2015
Dimensionality Reduction via Regression in Hyperspectral Imagery.
IEEE J. Sel. Top. Signal Process., 2015

Learning Structures in Earth Observation Data with Gaussian Processes.
Proceedings of the Advanced Analysis and Learning on Temporal Data, 2015

Spatial/spectral information trade-off in hyperspectral images.
Proceedings of the 2015 IEEE International Geoscience and Remote Sensing Symposium, 2015

Large-scale random features for kernel regression.
Proceedings of the 2015 IEEE International Geoscience and Remote Sensing Symposium, 2015

2014
Principal Polynomial Analysis.
Int. J. Neural Syst., 2014

Dimensionality reduction via regression on hyperspectral infrared sounding data.
Proceedings of the 6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, 2014

Lossless coding of hyperspectral images with principal polynomial analysis.
Proceedings of the 2014 IEEE International Conference on Image Processing, 2014

2013
Encoding Invariances in Remote Sensing Image Classification With SVM.
IEEE Geosci. Remote. Sens. Lett., 2013

Kernel Structural SIMIlarity on hyperspectral images.
Proceedings of the 2013 IEEE International Geoscience and Remote Sensing Symposium, 2013

Chromatic induction and contrast masking: similar models, different goals?
Proceedings of the Human Vision and Electronic Imaging XVIII, 2013

Visual discrimination and adaptation using non-linear unsupervised learning.
Proceedings of the Human Vision and Electronic Imaging XVIII, 2013

2012
Nonlinearities and Adaptation of Color Vision from Sequential Principal Curves Analysis.
Neural Comput., 2012

Nonlinear data description with Principal Polynomial Analysis.
Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing, 2012

Including invariances in SVM remote sensing image classification.
Proceedings of the 2012 IEEE International Geoscience and Remote Sensing Symposium, 2012

2011
Iterative Gaussianization: From ICA to Random Rotations.
IEEE Trans. Neural Networks, 2011

Principal polynomial analysis for remote sensing data processing.
Proceedings of the 2011 IEEE International Geoscience and Remote Sensing Symposium, 2011

Kernel-based retrieval of atmospheric profiles from IASI data.
Proceedings of the 2011 IEEE International Geoscience and Remote Sensing Symposium, 2011

Complex-Valued Independent Component Analysis of Natural Images.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2011, 2011

2010
Psychophysically Tuned Divisive Normalization Approximately Factorizes the PDF of Natural Images.
Neural Comput., 2010

Image Denoising with Kernels Based on Natural Image Relations.
J. Mach. Learn. Res., 2010

Estimating biophysical variable dependences with kernels.
Proceedings of the IEEE International Geoscience & Remote Sensing Symposium, 2010

2009
Visual Cortex Performs a Sort of Non-linear ICA.
Proceedings of the Advances in Nonlinear Speech Processing, 2009

PCA Gaussianization for image processing.
Proceedings of the International Conference on Image Processing, 2009

2008
Recovering wavelet relations using SVM for image denoising.
Proceedings of the International Conference on Image Processing, 2008


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