Publicaciones en las que colabora con PABLO MORALES ÁLVAREZ (24)

2024

  1. An end-to-end approach to combine attention feature extraction and Gaussian Process models for deep multiple instance learning in CT hemorrhage detection

    Expert Systems with Applications, Vol. 240

  2. Focused active learning for histopathological image classification

    Medical Image Analysis, Vol. 95

  3. Hyperbolic Secant representation of the logistic function: Application to probabilistic Multiple Instance Learning for CT intracranial hemorrhage detection

    Artificial Intelligence, Vol. 331

  4. Introducing instance label correlation in multiple instance learning. Application to cancer detection on histopathological images

    Pattern Recognition, Vol. 146

  5. Learning from crowds for automated histopathological image segmentation

    Computerized Medical Imaging and Graphics, Vol. 112

  6. Probabilistic Attention Based on Gaussian Processes for Deep Multiple Instance Learning

    IEEE Transactions on Neural Networks and Learning Systems, Vol. 35, Núm. 8, pp. 10909-10922

2023

  1. Bibliometric analysis of the global scientific production on machine learning applied to different cancer types

    Environmental Science and Pollution Research, Vol. 30, Núm. 42, pp. 96125-96137

  2. Crowdsourcing Segmentation of Histopathological Images Using Annotations Provided by Medical Students

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

  3. Deep Gaussian Processes for Classification With Multiple Noisy Annotators. Application to Breast Cancer Tissue Classification

    IEEE Access, Vol. 11, pp. 6922-6934

  4. Probabilistic Modeling of Inter- and Intra-observer Variability in Medical Image Segmentation

    Proceedings of the IEEE International Conference on Computer Vision

  5. Probabilistic fusion of crowds and experts for the search of gravitational waves

    Knowledge-Based Systems, Vol. 261

  6. Smooth Attention for Deep Multiple Instance Learning: Application to CT Intracranial Hemorrhage Detection

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

2022

  1. Scalable Variational Gaussian Processes for Crowdsourcing: Glitch Detection in LIGO

    IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 44, Núm. 3, pp. 1534-1551

2021

  1. ACTIVATION-LEVEL UNCERTAINTY IN DEEP NEURAL NETWORKS

    ICLR 2021 - 9th International Conference on Learning Representations

  2. Learning from crowds in digital pathology using scalable variational Gaussian processes

    Scientific Reports, Vol. 11, Núm. 1

2020

  1. Deep Gaussian processes for biogeophysical parameter retrieval and model inversion

    ISPRS Journal of Photogrammetry and Remote Sensing, Vol. 166, pp. 68-81

  2. Development of New Machine Learning Models Based on Gaussian Processes. Applications to Remote Sensing and Astrophysics

    Development of New Machine Learning Models Based on Gaussian Processes. Applications to Remote Sensing and Astrophysics

2019

  1. Learning from crowds with variational Gaussian processes

    Pattern Recognition, Vol. 88, pp. 298-311

  2. Scalable and efficient learning from crowds with Gaussian processes

    Information Fusion, Vol. 52, pp. 110-127

2018

  1. Deep Gaussian processes for geophysical parameter retrieval

    International Geoscience and Remote Sensing Symposium (IGARSS)