5 citations · 11 across the 6 of their papers we have counts for
7 papers
A Scalable Approach to Probabilistic Neuro-Symbolic Robustness Verification
Vasileios Manginas, Nikolaos Manginas, Edward Stevinson +4
Neuro-Symbolic Artificial Intelligence (NeSy AI) has emerged as a promising direction for integrating neural learning with symbolic reasoning. Typically, in the probabilistic varia…
Learning Automata-Based Complex Event Patterns in Answer Set Programming
Nikos Katzouris, Georgios Paliouras
Complex Event Recognition and Forecasting (CER/F) techniques attempt to detect, or even forecast ahead of time, event occurrences in streaming input using predefined event patterns…
Artificial Intelligence Empowered Multiple Access for Ultra Reliable and Low Latency THz Wireless Networks
Alexandros-Apostolos A. Boulogeorgos, Edwin Yaqub, Rachana Desai +5
Terahertz (THz) wireless networks are expected to catalyze the beyond fifth generation (B5G) era. However, due to the directional nature and the line-of-sight demand of THz links,…
Online Learning Probabilistic Event Calculus Theories in Answer Set Programming
Nikos Katzouris, Alexander Artikis, Georgios Paliouras
Complex Event Recognition (CER) systems detect event occurrences in streaming time-stamped input using predefined event patterns. Logic-based approaches are of special interest in…
The Complex Event Recognition Group
Elias Alevizos, Alexander Artikis, Nikos Katzouris +2
The Complex Event Recognition (CER) group is a research team, affiliated with the National Centre of Scientific Research "Demokritos" in Greece. The CER group works towards advance…
Distributed Online Learning of Event Definitions
Nikos Katzouris, Alexander Artikis, Georgios Paliouras
Logic-based event recognition systems infer occurrences of events in time using a set of event definitions in the form of first-order rules. The Event Calculus is a temporal logic…
Incremental Learning of Event Definitions with Inductive Logic Programming
Nikos Katzouris, Alexander Artikis, George Paliouras
Event recognition systems rely on properly engineered knowledge bases of event definitions to infer occurrences of events in time. The manual development of such knowledge is a ted…