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About
About ESSAI
About SLAIS
About the organizers
Committees
Programme
Schedule
Keynote Lecture
ESSAI Courses
ACAI Tutorials
Programme
Call for course proposals
Photos
For participants
Registrations
Accommodation
Airport transfer
EurAI travel grants
ESSAI&ACAI venue
Location
Travel information
Travel
Gourmet experience
Excursions
Visas and general information
Sponsors
Under the auspices of
Organized by
Financially supported by
Contact
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Registrations
ESSAI Courses
01.
Large Language Models: Background and Applications
Michael Roth and Ivan Vulic
02.
Machines Climbing Pearl’s Ladder of Causation
Devendra Dhami, Matej Zecevic and Adele Ribeiro
03.
Formal Explainability in Artificial Intelligence
Alexey Ignatiev, Nina Narodytska and Joao Marques-Silva
04.
Introduction to computational argumentation semantics
Srdjan Vesic and Dragan Doder
05.
Statistical evaluation of the performance of machine learning models
Richard Dinga
06.
06.
Continual learning for image classification
Adrian Popescu
07.
Automated Verification of Multi-Agent Systems. Why, What, and Especially: How?
Catalin Dima and Wojtek Jamroga
08.
Game-Theoretic Approach to Planning and Synthesis
Antonio Di Stasio, Giuseppe Perelli and Shufang Zhu
09.
AI fairness and privacy: fundamentals, synergies and conflicts
Tijl De Bie and Maarten Buyl
10.
Temporal Reasoning in AI: an introduction
Nicola Gigante
11.
Model Uncertainty in Sequential Decision Making
Bruno Lacerda, Nick Hawes and Dave Parker
12.
AutoML: Accelerating Research on and Development of AI Applications
Marius Lindauer and Katharina Eggensperger
13.
Multi-Objective Reinforcement Learning
Roxana Radulescu
14.
From Statistical Relational to Neural Symbolic Artificial Intelligence
Sebastijan Dumancic, Robin Manhaeve and Giuseppe Marra
15.
Probabilistic Circuits: Deep Probabilistic Models with Reliable Reasoning
Robert Peharz and Antonio Vergari
16.
Knowledge representation and reasoning with ontologies
Pance Panov
17.
Machine Learning Beyond Static Datasets
Martin Mundt
18.
Foundations of Automated Planning
Roman Barták
19.
Explaining and Repairing Description Logic Ontologies
Franz Baader, Patrick Koopmann and Francesco Kriegel
20.
Pills of Answer Set Programming
Mario Alviano and Francesco Ricca
21.
Smart-sized Benchmarking for Black-Box Optimization
Tome Eftimov and Peter Korošec
22.
Practical Applications of Artificial Intelligence for Robotics
Timothy Wiley
23.
Learning to act and plan
Blai Bonet and Hector Geffner
24.
Uncertainty Quantification in Machine Learning
Marco Zullich and Matias Valdenegro-Toro
