Back to top

ILP Program (All times are CEST)

Monday 25

12:00 - 13:05
Logical Learning in Dynamic Domains

12:00 - 12:15
Journal TrackAshwin Srinivasan, Michael Bain and A. Baskar
Learning Explanations for Biological Feedback with Delays Using an Event Calculus
12:15 - 12:30
Journal TrackTony Ribeiro, Maxime Folschette, Morgan Magnin, Katsumi Inoue
Learning Any Memoryless Discrete Semantics for Dynamical Systems Represented by Logic Programs
12:30 - 12:45
Journal TrackKun Gao, Hanpin Wang, Yongzhi Cao and Katsumi Inoue
Learning from Interpretation Transition Using Differentiable Logic Programming Semantics
12:45 - 12:55
Conference Track Oliver Ray
Learning and Revising Dynamic Temporal Theories in the Full Discrete Event Calculus
12:55 - 13:05
Conference TrackVictor Guimarães and Vítor Costa
Online Learning of Logic-Based Neural Network Structures

16:30 - 17:35
Logic and Learning

16:30 - 16:45
Journal TrackLun Ai, Stephen H. Muggleton, Céline Hocquette, Mark Gromowski, Ute Schmid
Beneficial and Harmful Explanatory Machine Learning
16:45 - 17:00
Journal TrackStassa Patsantzis, Stephen H. Muggleton
Top Program Construction and Reduction for Polynomial Time Meta-Interpretive Learning
17:00 - 17:15
Journal TrackJohannes Rabold, Michael Siebers, Ute Schmid
Generating Contrastive Explanations for Inductive Logic Programming Based on a Near Miss Approach
17:15 - 17:25
Conference Track Dany Varghese, Roman Bauer, Daniel Baxter-Beard, Stephen Muggleton and Alireza Tamaddoni-Nezhad
Human-like rule learning from images using one-shot hypothesis derivation
17:25 - 17:35
Conference TrackDidac Barroso-Bergada, Alireza Tamaddoni-Nezhad, Stephen H. Muggleton, Corinne Vacher, Nika Galic and David A. Bohan
Machine learning of microbial interactions using Abductive ILP and Hypothesis Frequency/Compression Estimation

Tuesday 26

12:00 - 13:00: ILP Session
Logical and Neural Learning

12:00 - 12:15
Journal TrackMichele Fraccaroli, Evelina Lamma, Fabrizio Riguzzi
Symbolic DNN-Tuner
12:15 - 12:30
Journal TrackTirtharaj Dash, Ashwin Srinivasan and Anguraj Baskar
Inclusion of Domain-Knowledge into GNNs using Mode-Directed Inverse Entailment
12:30 - 12:40
Conference TrackTirtharaj Dash, Ashwin Srinivasan, Lovekesh Vig and Arijit Roy
Using Domain-Knowledge to Assist Lead Discovery in Early-Stage Drug Design
12:40 - 12:50
Conference TrackYin Jun Phua and Katsumi Inoue
Learning Logic Programs Using Neural Networks by Exploiting Symbolic Invariance
12:50 - 13:00
Conference TrackCristina Cornelio and Veronika Thost
Synthetic Datasets and Evaluation Tools for Inductive Neural Reasoning

16:30 - 17:45
Graphs and Ontologies

16:30 - 16:45
Journal TrackBlaž Škrlj, Matej Martinc, Nada Lavrač & Senja Pollak
autoBOT: evolving neuro‑symbolic representations for explainable low resource text classifcation
16:45 - 16:55
Conference Track Devendra Dhami, Siwen Yan, Gautam Kunapuli and Sriraam Natarajan
Non-Parametric Learning of Embeddings for Relational Data using Gaifman Locality Theorem
16:55 - 17:05
Conference Track Thais Luca, Aline Paes and Gerson Zaverucha
Mapping Across Relational Domains for Transfer Learning with Word Embeddings-based Similarity
17:05 - 17:15
Conference TrackLeticia Figueiredo, Aline Paes and Gerson Zaverucha
Transfer Learning for Boosted Relational Dependency Networks Through a Genetic Algorithm
17:15 - 17:25
Conference TrackPatrick Westphal, Sahar Vahdati and Jens Lehmann
A Simulated Annealing Meta-heuristic for Concept Learning in Description Logics
17:25 - 17:35
Conference TrackClaudia d'Amato, Nicola Flavio Quatraro and Nicola Fanizzi
Embedding Models for Knowledge Graphs Induced by Clusters of Relations and Background Knowledge
17:35 - 17:45
Conference TrackCan Erten and Dimitar Kazakov
Ontology Graph Embeddings and ILP for Financial Forecasting

Wednesday 27

12:00 - 13:00
Learning in Answer Set Programming

12:00 - 12:15
Journal TrackAndrew Cropper and Rolf Morel
Learning Programs by Learning from Failures
12:15 - 12:30
Journal TrackAlice Tarzariol, Martin Gebser, Konstantin Schekotihin
Lifting Symmetry Breaking Constraints with Inductive Logic Programming
12:30 - 12:45
Journal TrackDaniele Meli, Mohan Sridharan, Paolo Fiorini
Inductive Learning of Answer Set Programs for Autonomous Surgical Task Planning - Application to a Training Task for Surgeons
12:45 - 13:00
Recently Published - IJCAI 2021Mark Law, Alessandra Russo, Krysia Broda and Elisa Bertino
Scalable Non-observational Predicate Learning in ASP

13:30 - 14:30
Probabilistic Logical Learning

13:30 - 13:45
Journal TrackFabrizio Riguzzi, Elena Bellodi, Riccardo Zese, Marco Alberti and Evelina Lamma
Probabilistic Inductive Constraint Logic
13:45 - 14:00
Journal TrackArnaud Nguembang Fadja, Fabrizio Riguzzi and Evelina Lamma
Learning Hierarchical Probabilistic Logic Programs
14:00 - 14:10
Recently Published - AIJ 2021Damiano Azzolini, Fabrizio Riguzzi and Evelina Lamma
A Semantics for Hybrid Probabilistic Logic Programs with Function Symbols
14:10 - 14:20
Recently Published - TPLP 2021Felix Weitkämper
An Asymptotic Analysis of Probabilistic Logic Programming, with Implications for Expressing Projective Families of Distributions
14:20 - 14:30
Conference TrackFabrizio Ventola, Devendra Dhami and Kristian Kersting
Generative Clausal Networks: Relational Decision Trees as Probabilistic Circuits

Short Papers and Late-Breaking Abstracts (posters only)
ShortFlorian Andreas Marwitz, Tanya Braun and Ralf Möller
A First Step Towards Even More Sparse Encodings of Probability Distributions
ShortHien Nguyen and Chiaki Sakama
Feature Learning by Least Generalization
ShortJáchym Barvínek, Timothy van Bremen, Yuyi Wang, Filip Železný and Ondřej Kuželka
Automatic Conjecturing of P-Recursions Using Lifted Inference
Late-breakingOmar Iken, Maxime Folschette and Tony Ribeiro
Automatic Modeling of Dynamical Interactions Within Marine Ecosystems
Late-breakingTony Ribeiro, Maxime Folschette, Morgan Magnin and Katsumi Inoue
Polynomial Algorithm For Learning From Interpretation Transition
Late-breakingMark Gromowski, Dennis Müller and Ute Schmid
Exploiting Temporal Relations of Events for Classification Tasks – Proof of Concept Study with Synthetic Data Sets