13 citations · 19 across the 10 of their papers we have counts for
11 papers
Visualizing Uncertainty-to-Action Composition for Human Oversight
Chisom Anyabolu, Akshat Dubey, Georges Hattab
Artificial intelligence systems often disclose uncertainty, yet they rarely make clear what response that uncertainty should trigger. Most uncertainty visualizations encode uncerta…
A Multi-Technique Approach for Improving Summary Polar Diagrams
Aleksandar Anžel, Zewen Yang, Georges Hattab
While the polar system may lack the universal familiarity of its Cartesian counterpart, it remains indispensable for certain tasks. Summary polar diagrams, such as Taylor and mutua…
PepTriX: A Framework for Explainable Peptide Analysis through Protein Language Models
Vincent Schilling, Akshat Dubey, Georges Hattab
Peptide classification tasks, such as predicting toxicity and HIV inhibition, are fundamental to bioinformatics and drug discovery. Traditional approaches rely heavily on handcraft…
The Open Syndrome Definition
Ana Paula Gomes Ferreira, Aleksandar Anžel, Izabel Oliva Marcilio de Souza +6
Case definitions are essential for effectively communicating public health threats. However, the absence of a standardized, machine-readable format poses significant challenges to…
Surrogate Interpretable Graph for Random Decision Forests
Akshat Dubey, Aleksandar Anžel, Georges Hattab
The field of health informatics has been profoundly influenced by the development of random forest models, which have led to significant advances in the interpretability of feature…
AI Readiness in Healthcare through Storytelling XAI
Akshat Dubey, Zewen Yang, Georges Hattab
Artificial Intelligence is rapidly advancing and radically impacting everyday life, driven by the increasing availability of computing power. Despite this trend, the adoption of AI…
A Nested Model for AI Design and Validation
Akshat Dubey, Zewen Yang, Georges Hattab
The growing AI field faces trust, transparency, fairness, and discrimination challenges. Despite the need for new regulations, there is a mismatch between regulatory science and AI…
Kernel-based Learning for Safe Control of Discrete-Time Unknown Systems under Incomplete Observations
Zewen Yang, Xiaobing Dai, Weijie Yang +3
Safe control for dynamical systems is critical, yet the presence of unknown dynamics poses significant challenges. In this paper, we present a learning-based control approach for t…
Decentralized Event-Triggered Online Learning for Safe Consensus of Multi-Agent Systems with Gaussian Process Regression
Xiaobing Dai, Zewen Yang, Mengtian Xu +3
Consensus control in multi-agent systems has received significant attention and practical implementation across various domains. However, managing consensus control under unknown d…
Cooperative Learning with Gaussian Processes for Euler-Lagrange Systems Tracking Control under Switching Topologies
Zewen Yang, Songbo Dong, Armin Lederer +5
This work presents an innovative learning-based approach to tackle the tracking control problem of Euler-Lagrange multi-agent systems with partially unknown dynamics operating unde…
Whom to Trust? Elective Learning for Distributed Gaussian Process Regression
Zewen Yang, Xiaobing Dai, Akshat Dubey +2
This paper introduces an innovative approach to enhance distributed cooperative learning using Gaussian process (GP) regression in multi-agent systems (MASs). The key contribution…