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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
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Registrations
Invited Speaker
Jure Leskovec
Deep Learning for Relational Data: Graph Neural Networks and Beyond
Speakers
Devendra Dhami
Machines Climbing Pearl’s Ladder of Causation
Alexey Ignatiev
Formal Explainability in Artificial Intelligence
Marius Lindauer
AutoML: Accelerating Research on and Development of AI Applications
michael roth
Large Language Models: Background and Applications
Matej Zečević
Machines Climbing Pearl’s Ladder of Causation
Srdjan Vesić
Introduction to computational argumentation semantics
Joao Marques-Silva
Formal Explainability in Artificial Intelligence
Giuseppe Perelli
Game-Theoretic Approach to Planning and Synthesis
Giuseppe Perelli
Game-Theoretic Approach to Planning and Synthesis
Adrian Popescu
Continual learning for image classification
Dragan Doder
Introduction to computational argumentation semantics
Richard Dinga
Statistical evaluation of the performance of machine learning models
Ivan Vulic
Large Language Models: Background and Applications
Adèle Helena Ribeiro
Machines Climbing Pearl’s Ladder of Causation
Wojtek Jamroga
Automated Verification of Multi-Agent Systems. Why, What, and Especially: How?
Antonio Di Stasio
Game-Theoretic Approach to Planning and Synthesis
Tijl De Bie
AI fairness and privacy: fundamentals, synergies and conflicts
Shufang Zhu
Game-Theoretic Approach to Planning and Synthesis
Catalin Dima
Automated Verification of Multi-Agent Systems. Why, What, and Especially: How?
Nicola Gigante
Temporal Reasoning in AI: an introduction
Bruno Lacerda
Model Uncertainty in Sequential Decision Making
Maarten Buyl
AI fairness and privacy: fundamentals, synergies and conflicts
Katharina Eggensperger
AutoML: Accelerating Research on and Development of AI Applications
Roxana Rădulescu
Multi-Objective Reinforcement Learning
Sebastijan Dumančić
From Statistical Relational to Neural Symbolic Artificial Intelligence
Nick Hawes
Model Uncertainty in Sequential Decision Making
David Parker
Model Uncertainty in Sequential Decision Making
Robert Peharz
Probabilistic Circuits: Deep Probabilistic Models with Reliable Reasoning
Roman Barták
Foundations of Automated Planning
Panče Panov
Knowledge representation and reasoning with ontologies
Martin Mundt
Machine Learning Beyond Static Datasets
Nina Narodytska
Formal Explainability in Artificial Intelligence
Robin Manhaeve
From Statistical Relational to Neural Symbolic Artificial Intelligence
Antonio Vergari
Probabilistic Circuits: Deep Probabilistic Models with Reliable Reasoning
Timothy Wiley
Practical Applications of Artificial Intelligence for Robotics
Tome Eftimov
Smart-sized Benchmarking for Black-Box Optimization
Nathan Kutz
The future of governing equations
Franz Baader
Explaining and Repairing Description Logic Ontologies
Mario Alviano
Pills of Answer Set Programming
Marco Zullich
Uncertainty Quantification in Machine Learning
Giuseppe Marra
From Statistical Relational to Neural Symbolic Artificial Intelligence
Patrick Koopmann
Explaining and Repairing Description Logic Ontologies
Francesco Ricca
Pills of Answer Set Programming
Blai Bonet
Learning to act and plan
Peter Korošec
Smart-sized Benchmarking for Black-Box Optimization
Roger Guimerà
Bayesian approaches to symbolic regression and equation discovery
Hector Geffner
Learning to act and plan
Francesco Kriegel
Explaining and Repairing Description Logic Ontologies
Pat Langley
Computational Scientific Discovery and Process-Based Modelling
Julio Rodriguez Banga
Automated modelling and design of dynamical systems in the life sciences
Matias Valdenegro-Toro
Uncertainty Quantification in Machine Learning
Gustau Camps-Valls
Advanced machine (not deep) learning for modeling and understanding the Earth system
žiga Avsec
AI for Biology and Science
Arman Cohan
Language Modeling for Science
Clare Bycroft
AI for Biology and Science
Ross King
Closed-Loop Automation of Scientific Research
Claudio Zeni
Machine Learning Force Fields in Materials Science
Vedran Dunjko
Basic Ideas in Quantum Machine Learning
Michel Dumontier
Symbolic AI with Knowledge Graphs and Ontologies
The promise and perils of FAIR Data
Larisa Soldatova
Formalisation of Scientific Knowledge
