Pablo Morales-Alvarez

Orcid: 0000-0003-2793-0083

According to our database1, Pablo Morales-Alvarez authored at least 21 papers between 2016 and 2024.

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Bibliography

2024
Introducing instance label correlation in multiple instance learning. Application to cancer detection on histopathological images.
Pattern Recognit., February, 2024

Hyperbolic Secant representation of the logistic function: Application to probabilistic Multiple Instance Learning for CT intracranial hemorrhage detection.
CoRR, 2024

2023
Probabilistic fusion of crowds and experts for the search of gravitational waves.
Knowl. Based Syst., 2023

Probabilistic Attention based on Gaussian Processes for Deep Multiple Instance Learning.
CoRR, 2023

Deep Gaussian Processes for Classification With Multiple Noisy Annotators. Application to Breast Cancer Tissue Classification.
IEEE Access, 2023

Smooth Attention for Deep Multiple Instance Learning: Application to CT Intracranial Hemorrhage Detection.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

Probabilistic Modeling of Inter- and Intra-observer Variability in Medical Image Segmentation.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Crowdsourcing Segmentation of Histopathological Images Using Annotations Provided by Medical Students.
Proceedings of the Artificial Intelligence in Medicine, 2023

2022
Scalable Variational Gaussian Processes for Crowdsourcing: Glitch Detection in LIGO.
IEEE Trans. Pattern Anal. Mach. Intell., 2022

Simultaneous Missing Value Imputation and Structure Learning with Groups.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021
VICause: Simultaneous Missing Value Imputation and Causal Discovery with Groups.
CoRR, 2021

Deep Gaussian Processes for Biogeophysical Parameter Retrieval and Model Inversion.
CoRR, 2021

Activation-level uncertainty in deep neural networks.
Proceedings of the 9th International Conference on Learning Representations, 2021

2019
Learning from crowds with variational Gaussian processes.
Pattern Recognit., 2019

Scalable and efficient learning from crowds with Gaussian processes.
Inf. Fusion, 2019

2018
Remote Sensing Image Classification With Large-Scale Gaussian Processes.
IEEE Trans. Geosci. Remote. Sens., 2018

Deep Gaussian Processes for Geophysical Parameter Retrieval.
Proceedings of the 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018

2017
The NoiseFiltersR Package: Label Noise Preprocessing in R.
R J., 2017

Efficient remote sensing image classification with Gaussian processes and Fourier features.
Proceedings of the 2017 IEEE International Geoscience and Remote Sensing Symposium, 2017

Passive millimeter wave image classification with large scale Gaussian processes.
Proceedings of the 2017 IEEE International Conference on Image Processing, 2017

2016
A First Study on the Use of Boosting for Class Noise Reparation.
Proceedings of the Hybrid Artificial Intelligent Systems - 11th International Conference, 2016


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