339 citations · 686 across the 11 of their papers we have counts for
5 papers · 1 filter
Class-Discriminative Attention Maps for Vision Transformers
Lennart Brocki, Jakub Binda, Neo Christopher Chung
Importance estimators are explainability methods that quantify feature importance for deep neural networks (DNN). In vision transformers (ViT), the self-attention mechanism natural…
Challenges of Large Language Models for Mental Health Counseling
Neo Christopher Chung, George Dyer, Lennart Brocki
The global mental health crisis is looming with a rapid increase in mental disorders, limited resources, and the social stigma of seeking treatment. As the field of artificial inte…
Integration of Radiomics and Tumor Biomarkers in Interpretable Machine Learning Models
Lennart Brocki, Neo Christopher Chung
Despite the unprecedented performance of deep neural networks (DNNs) in computer vision, their practical application in the diagnosis and prognosis of cancer using medical imaging…
Feature Perturbation Augmentation for Reliable Evaluation of Importance Estimators in Neural Networks
Lennart Brocki, Neo Christopher Chung
Post-hoc explanation methods attempt to make the inner workings of deep neural networks more interpretable. However, since a ground truth is in general lacking, local post-hoc inte…
Deep Learning Mental Health Dialogue System
Lennart Brocki, George C. Dyer, Anna Gładka +1
Mental health counseling remains a major challenge in modern society due to cost, stigma, fear, and unavailability. We posit that generative artificial intelligence (AI) models des…