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Probabilistic Attention based on Gaussian Processes for Deep Multiple Instance Learning., , and . CoRR, (2023)Scalable Variational Gaussian Processes for Crowdsourcing: Glitch Detection in LIGO., , , , and . IEEE Trans. Pattern Anal. Mach. Intell., 44 (3): 1534-1551 (2022)Probabilistic Modeling of Inter- and Intra-observer Variability in Medical Image Segmentation., , and . ICCV, page 21040-21049. IEEE, (2023)Deep Gaussian Processes for geophysical parameter retrieval., , , and . CoRR, (2020)Smooth Attention for Deep Multiple Instance Learning: Application to CT Intracranial Hemorrhage Detection., , , , and . MICCAI (5), volume 14224 of Lecture Notes in Computer Science, page 327-337. Springer, (2023)Introducing instance label correlation in multiple instance learning. Application to cancer detection on histopathological images., , , and . Pattern Recognit., (February 2024)The NoiseFiltersR Package: Label Noise Preprocessing in R., , , , , and . R J., 9 (1): 219 (2017)Crowdsourcing Segmentation of Histopathological Images Using Annotations Provided by Medical Students., , , , and . AIME, volume 13897 of Lecture Notes in Computer Science, page 245-249. Springer, (2023)Introducing instance label correlation in multiple instance learning. Application to cancer detection on histopathological images., , , and . CoRR, (2023)Deep Gaussian Processes for Classification With Multiple Noisy Annotators. Application to Breast Cancer Tissue Classification., , , , and . IEEE Access, (2023)