The GCE in a New Light: Disentangling the γ-ray Sky with Bayesian Graph Convolutional Neural Networks. - Florian List; Nicholas L. Rodd; Geraint F. Lewis; Ishaan Bhat (CoRR, 2020)

Extending Probabilistic U-Net Using MC-Dropout to Quantify Data and Model Uncertainty. - Ishaan Bhat; Hugo J. Kuijf (BrainLes@MICCAI (2), 2021)

Using Uncertainty Estimation To Reduce False Positives In Liver Lesion Detection. - Ishaan Bhat; Hugo J. Kuijf; Veronika Cheplygina; Josien P. W. Pluim (ISBI, 2021)

Generalized Probabilistic U-Net for Medical Image Segementation. - Ishaan Bhat; Josien P. W. Pluim; Hugo J. Kuijf (UNSURE@MICCAI, 2022)

Influence of uncertainty estimation techniques on false-positive reduction in liver lesion detection. - Ishaan Bhat; Josien P. W. Pluim; Max A. Viergever; Hugo J. Kuijf (CoRR, 2022)

Calibration techniques for node classification using graph neural networks on medical image data. - Iris N. Vos; Ishaan Bhat; Birgitta K. Velthuis; Ynte M. Ruigrok; Hugo J. Kuijf (MIDL, 2023)

Effect of latent space distribution on the segmentation of images with multiple annotations. - Ishaan Bhat; Josien P. W. Pluim; Max A. Viergever; Hugo J. Kuijf (CoRR, 2023)

QUBIQ: Uncertainty Quantification for Biomedical Image Segmentation Challenge. - Hongwei Bran Li; Fernando Navarro; Ivan Ezhov; Amirhossein Bayat; Dhritiman Das; Florian Kofler; Suprosanna Shit; Diana Waldmannstetter; Johannes C. Paetzold; Xiaobin Hu; Benedikt Wiestler; Lucas Zimmer; et al. (CoRR, 2024)