From the 1 of 6 linked papers with an AI index.
6 papers
Beyond Points: Spherical Distributional Part Prototypes for Interpretable Classification
Duarte Leão, Diogo Pereira Araújo, Catarina Barata +1
The paper introduces vMFProto, a prototype‑based model that represents each class as a mixture of von Mises‑Fisher distributions on the unit sphere, enabling more stable and interp…
Locating Demographic Bias at the Attention-Head Level in CLIP's Vision Encoder
Alaa Yasser, Kittipat Phunjanna, Marcos Escudero Viñolo +2
Standard fairness audits of foundation models quantify that a model is biased, but not where inside the network the bias resides. We propose a mechanistic fairness audit that combi…
MIL vs. Aggregation: Evaluating Patient-Level Survival Prediction Strategies Using Graph-Based Learning
M Rita Verdelho, Alexandre Bernardino, Catarina Barata
Oncologists often rely on a multitude of data, including whole-slide images (WSIs), to guide therapeutic decisions, aiming for the best patient outcome. However, predicting the pro…
The Role of Graph-based MIL and Interventional Training in the Generalization of WSI Classifiers
Rita Pereira, M. Rita Verdelho, Catarina Barata +1
Whole Slide Imaging (WSI), which involves high-resolution digital scans of pathology slides, has become the gold standard for cancer diagnosis, but its gigapixel resolution and the…
Continual Deep Active Learning for Medical Imaging: Replay-Base Architecture for Context Adaptation
Rui Daniel, M. Rita Verdelho, Catarina Barata +1
Deep Learning for medical imaging faces challenges in adapting and generalizing to new contexts. Additionally, it often lacks sufficient labeled data for specific tasks requiring s…
Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation
Kirill Sirotkin, Marcos Escudero-Viñolo, Pablo Carballeira +3
Foundation models trained on web-scraped datasets propagate societal biases to downstream tasks. While counterfactual generation enables bias analysis, existing methods introduce a…