4 citations · 5 across the 7 of their papers we have counts for
7 papers
The Unified Evaluation App for DNA Data Storage Codecs
Aleksandar Anžel, Chisom Anyabolu, Leon Wimbes +12
Background: Deoxyribonucleic acid (DNA) data storage is a paradigm with great potential for ultra-dense and durable information preservation. However, the rapid proliferation of co…
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…
UbiQVision: Quantifying Uncertainty in XAI for Image Recognition
Akshat Dubey, Aleksandar Anžel, Bahar İlgen +1
Recent advances in deep learning have led to its widespread adoption across diverse domains, including medical imaging. This progress is driven by increasingly sophisticated model…
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…
UbiQTree: Uncertainty Quantification in XAI with Tree Ensembles
Akshat Dubey, Aleksandar Anžel, Bahar İlgen +1
Explainable Artificial Intelligence (XAI) techniques, such as SHapley Additive exPlanations (SHAP), have become essential tools for interpreting complex ensemble tree-based models,…
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…
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…