31 citations · 89 across the 21 of their papers we have counts for
6 papers · 1 filter
SI-MIL: Taming Deep MIL for Self-Interpretability in Gigapixel Histopathology
Saarthak Kapse, Pushpak Pati, Srijan Das +7
Introducing interpretability and reasoning into Multiple Instance Learning (MIL) methods for Whole Slide Image (WSI) analysis is challenging, given the complexity of gigapixel slid…
Hybrid quantum-classical graph neural networks for tumor classification in digital pathology
Anupama Ray, Dhiraj Madan, Srushti Patil +2
Advances in classical machine learning and single-cell technologies have paved the way to understand interactions between disease cells and tumor microenvironments to accelerate th…
Towards quantum-enabled cell-centric therapeutics
Saugata Basu, Jannis Born, Aritra Bose +30
In recent years, there has been tremendous progress in the development of quantum computing hardware, algorithms and services leading to the expectation that in the near future qua…
Generative appearance replay for continual unsupervised domain adaptation
Boqi Chen, Kevin Thandiackal, Pushpak Pati +1
Deep learning models can achieve high accuracy when trained on large amounts of labeled data. However, real-world scenarios often involve several challenges: Training data may beco…
Multi-scale Feature Alignment for Continual Learning of Unlabeled Domains
Kevin Thandiackal, Luigi Piccinelli, Pushpak Pati +1
Methods for unsupervised domain adaptation (UDA) help to improve the performance of deep neural networks on unseen domains without any labeled data. Especially in medical disciplin…
Weakly Supervised Joint Whole-Slide Segmentation and Classification in Prostate Cancer
Pushpak Pati, Guillaume Jaume, Zeineb Ayadi +4
The segmentation and automatic identification of histological regions of diagnostic interest offer a valuable aid to pathologists. However, segmentation methods are hampered by the…