most citedIncremental Fingerprinting in an Open World

1 citations · 1 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CR20261 cited

Incremental Fingerprinting in an Open World

Loes Kruger, Paul Kobialka, Andrea Pferscher +3

Network protocol fingerprinting is used to identify a protocol implementation by analyzing its input-output behavior. Traditionally, fingerprinting operates under a closed-world as…

cs.AI2026

Attribution-based Explanations for Markov Decision Processes

Paul Kobialka, Andrea Pferscher, Francesco Leofante +3

Attribution techniques explain the outcome of an AI model by assigning a numerical score to its inputs. So far, these techniques have mainly focused on attributing importance to st…

cs.SE2026

Automata Learning versus Process Mining: The Case for User Journeys

Paul Kobialka, Andrea Pferscher, Bernhard K. Aichernig +2

With the servitization of business, understanding how users experience services becomes a crucial success factor for companies. Therefore, there is a need to include feedback from…

cs.AI2025

Counterfactual Strategies for Markov Decision Processes

Paul Kobialka, Lina Gerlach, Francesco Leofante +3

Counterfactuals are widely used in AI to explain how minimal changes to a model's input can lead to a different output. However, established methods for computing counterfactuals t…

cs.AI2025

BedreFlyt: Improving Patient Flows through Hospital Wards with Digital Twins

Riccardo Sieve, Paul Kobialka, Laura Slaughter +3

Digital twins are emerging as a valuable tool for short-term decision-making as well as for long-term strategic planning across numerous domains, including process industry, energy…