A First Study on the Use of Boosting for Class Noise Reparation. - Pablo Morales-Alvarez; Julián Luengo; Francisco Herrera (HAIS, 2016)

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)

The NoiseFiltersR Package: Label Noise Preprocessing in R. - Pablo Morales-Álvarez; Julián Luengo; Luís Paulo F. Garcia; Ana Carolina Lorena; André C. P. L. F. de Carvalho; Francisco Herrera (R J., 2017)

Deep Gaussian Processes for Geophysical Parameter Retrieval. - Daniel Heestermans Svendsen; Pablo Morales-Alvarez; Rafael Molina 001; Gustau Camps-Valls (IGARSS, 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)

Scalable and efficient learning from crowds with Gaussian processes. - Pablo Morales-Alvarez; Pablo Ruiz 002; Raúl Santos-Rodríguez; Rafael Molina 001; Aggelos K. Katsaggelos (Inf. Fusion, 2019)

Learning from crowds with variational Gaussian processes. - Pablo Ruiz 002; Pablo Morales-Alvarez; Rafael Molina 001; Aggelos K. Katsaggelos (Pattern Recognit., 2019)

Development of New Machine Learning Models Based on Gaussian Processes. Applications to Remote Sensing and Astrophysics. - Pablo Morales-Alvarez (2020)

Activation-level uncertainty in deep neural networks. - Pablo Morales-Alvarez; Daniel Hernández-Lobato; Rafael Molina 001; José Miguel Hernández-Lobato (ICLR, 2021)

Deep Gaussian Processes for Biogeophysical Parameter Retrieval and Model Inversion. - Daniel Heestermans Svendsen; Pablo Morales-Alvarez; Ana Belen Ruescas; Rafael Molina 001; Gustau Camps-Valls (CoRR, 2021)

VICause: Simultaneous Missing Value Imputation and Causal Discovery with Groups. - Pablo Morales-Alvarez; Angus Lamb; Simon Woodhead 002; Simon Peyton Jones; Miltiadis Allamanis; Cheng Zhang 005 (CoRR, 2021)

Simultaneous Missing Value Imputation and Structure Learning with Groups. - Pablo Morales-Alvarez; Wenbo Gong 001; Angus Lamb; Simon Woodhead 002; Simon Peyton Jones; Nick Pawlowski; Miltiadis Allamanis; Cheng Zhang 005 (NeurIPS, 2022)

Scalable Variational Gaussian Processes for Crowdsourcing: Glitch Detection in LIGO. - Pablo Morales-Álvarez; Pablo Ruiz 002; Scott Coughlin; Rafael Molina 001; Aggelos K. Katsaggelos (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

Crowdsourcing Segmentation of Histopathological Images Using Annotations Provided by Medical Students. - Miguel López-Pérez; Pablo Morales-Álvarez; Lee A. D. Cooper; Rafael Molina 001; Aggelos K. Katsaggelos (AIME, 2023)

Probabilistic Modeling of Inter- and Intra-observer Variability in Medical Image Segmentation. - Arne Schmidt 005; Pablo Morales-Álvarez; Rafael Molina 001 (ICCV, 2023)

Smooth Attention for Deep Multiple Instance Learning: Application to CT Intracranial Hemorrhage Detection. - Yunan Wu; Francisco M. Castro-Macías; Pablo Morales-Álvarez; Rafael Molina 001; Aggelos K. Katsaggelos (MICCAI (5), 2023)

Deep Gaussian Processes for Classification With Multiple Noisy Annotators. Application to Breast Cancer Tissue Classification. - Miguel López-Pérez; Pablo Morales-Álvarez; Lee A. D. Cooper; Rafael Molina 001; Aggelos K. Katsaggelos (IEEE Access, 2023)

Probabilistic fusion of crowds and experts for the search of gravitational waves. - Pablo Ruiz 002; Pablo Morales-Álvarez; Scott Coughlin; Rafael Molina 001; Aggelos K. Katsaggelos (Knowl. Based Syst., 2023)

Sm: enhanced localization in Multiple Instance Learning for medical imaging classification. - Francisco M. Castro-Macías; Pablo Morales-Alvarez; Yunan Wu; Rafael Molina 001; Aggelos K. Katsaggelos (NeurIPS, 2024)

Hyperbolic Secant representation of the logistic function: Application to probabilistic Multiple Instance Learning for CT intracranial hemorrhage detection. - Francisco M. Castro-Macías; Pablo Morales-Álvarez; Yunan Wu; Rafael Molina 001; Aggelos K. Katsaggelos (Artif. Intell., 2024)

Learning from crowds for automated histopathological image segmentation. - Miguel López-Pérez; Pablo Morales-Álvarez; Lee A. D. Cooper; Christopher Felicelli; Jeffery A. Goldstein; Brian Vadasz; Rafael Molina 001; Aggelos K. Katsaggelos (Comput. Medical Imaging Graph., 2024)

BayesAdapter: enhanced uncertainty estimation in CLIP few-shot adaptation. - Pablo Morales-Álvarez; Stergios Christodoulidis; Maria Vakalopoulou; Pablo Piantanida; Jose Dolz (CoRR, 2024)

An end-to-end approach to combine attention feature extraction and Gaussian Process models for deep multiple instance learning in CT hemorrhage detection. - Jose Pérez-Cano; Yunan Wu; Arne Schmidt 005; Miguel López-Pérez; Pablo Morales-Álvarez; Rafael Molina 001; Aggelos K. Katsaggelos (Expert Syst. Appl., 2024)

Focused active learning for histopathological image classification. - Arne Schmidt 005; Pablo Morales-Álvarez; Lee A. D. Cooper; Lee A. Newberg; Andinet Enquobahrie; Rafael Molina 001; Aggelos K. Katsaggelos (Medical Image Anal., 2024)

Introducing instance label correlation in multiple instance learning. Application to cancer detection on histopathological images. - Pablo Morales-Álvarez; Arne Schmidt 005; José Miguel Hernández-Lobato; Rafael Molina 001 (Pattern Recognit., 2024)

Probabilistic Attention Based on Gaussian Processes for Deep Multiple Instance Learning. - Arne Schmidt 005; Pablo Morales-Álvarez; Rafael Molina 001 (IEEE Trans. Neural Networks Learn. Syst., 2024)

Probabilistic smooth attention for deep multiple instance learning in medical imaging. - Francisco M. Castro-Macías; Pablo Morales-Álvarez; Yunan Wu; Rafael Molina 001; Aggelos K. Katsaggelos (Pattern Recognit., 2026)