20 citations · 79 across the 11 of their papers we have counts for
13 papers
False Sense of Security in Explainable Artificial Intelligence (XAI)
Neo Christopher Chung, Hongkyou Chung, Hearim Lee +3
A cautious interpretation of AI regulations and policy in the EU and the USA place explainability as a central deliverable of compliant AI systems. However, from a technical perspe…
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…
Evaluation of importance estimators in deep learning classifiers for Computed Tomography
Lennart Brocki, Wistan Marchadour, Jonas Maison +5
Deep learning has shown superb performance in detecting objects and classifying images, ensuring a great promise for analyzing medical imaging. Translating the success of deep lear…
Fidelity of Interpretability Methods and Perturbation Artifacts in Neural Networks
Lennart Brocki, Neo Christopher Chung
Despite excellent performance of deep neural networks (DNNs) in image classification, detection, and prediction, characterizing how DNNs make a given decision remains an open probl…
Input Bias in Rectified Gradients and Modified Saliency Maps
Lennart Brocki, Neo Christopher Chung
Interpretation and improvement of deep neural networks relies on better understanding of their underlying mechanisms. In particular, gradients of classes or concepts with respect t…
BMS algebras in 4 and 3 dimensions, their quantum deformations and duals
A. Borowiec, L. Brocki, J. Kowalski-Glikman +1
BMS symmetry is a symmetry of asymptotically flat spacetimes in the vicinity of the null boundary of spacetime and it is expected to play a fundamental role in physics. It is inter…
Concept Saliency Maps to Visualize Relevant Features in Deep Generative Models
Lennart Brocki, Neo Christopher Chung
Evaluating, explaining, and visualizing high-level concepts in generative models, such as variational autoencoders (VAEs), is challenging in part due to a lack of known prediction…
Quantum ergosphere and brick wall entropy
Michele Arzano, Lennart Brocki, Jerzy Kowalski-Glikman +2
We revisit the "brick wall" model for black hole entropy taking into account back-reaction effects on the horizon structure. We do so by adopting an evaporating metric in the quasi…
-deformed BMS symmetry
A. Borowiec, L. Brocki, J. Kowalski-Glikman +1
We present the quantum -deformation of BMS symmetry, by generalizing the lightlike -Poincaré Hopf algebra. On the technical level, our analysis relies on the fact that the li…