publications

publications by categories in reversed chronological order. generated by jekyll-scholar.

2022

  1. Inductive Logic Programming At 30: A New Introduction
    Andrew Cropper, and Sebastijan Dumancic
    J. Artif. Intell. Res., 2022
  2. SaDe: Learning Models that Provably Satisfy Domain Constraints
    Kshitij Goyal, Sebastijan Dumancic, and Hendrik Blockeel
    ECMLPKDD, 2022

2021

  1. Automated Reasoning and Learning for Automated Payroll Management
    Sebastijan DumancicWannes Meert, Stijn Goethals, Tim Stuyckens, Jelle Huygen, and Koen Denies
    In Innovative Applications of Artificial Intelligence (IAAI), 2021
  2. Knowledge Refactoring for Inductive Program Synthesis
    Sebastijan DumancicTias Guns, and Andrew Cropper
    In AAAI Conference on Artificial Intelligence (AAAI), 2021
  3. Avatar - Automated Feature Wrangling for Machine Learning
    Gust Verbruggen, Elia Van Wolputte, Sebastijan Dumancic, and Luc De Raedt
    In Advances in Intelligent Data Analysis XIX - 19th International Symposium on Intelligent Data Analysis, IDA 2021, 2021
  4. Neural probabilistic logic programming in DeepProbLog
    Robin Manhaeve, Sebastijan Dumančić, Angelika KimmigThomas Demeester, and Luc De Raedt
    Artificial Intelligence, 2021
  5. Inductive logic programming at 30
    Andrew Cropper, Sebastijan Dumančić, Richard Evans, and Stephen Muggleton
    Machine Learning, 2021

2020

  1. Learning Large Logic Programs by Going Beyond Entailment
    Andrew Cropper, and Sebastijan Dumancic
    In International Joint Conference on Artificial Intelligence, 2020
  2. Turning 30: New Ideas in Inductive Logic Programming
    Andrew Cropper, and Sebastijan Dumancic
    In International Joint Conference on Artificial Intelligence, 2020
  3. From Statistical Relational to Neural-Symbolic Artificial Intelligence
    Luc De RaedtSebastijan Dumancic, Robin Manhaeve, and Giuseppe Marra
    In International Joint Conference on Artificial Intelligence, 2020
  4. Tackling Noise in Semi-Supervised Clustering
    Jonas Soenen, Sebastijan Dumancic, and Hendrik Blockeel
    In European Conference on Machine Learning and Principles of Knowledge Discovery in Databases (ECML), 2020

2019

  1. Learning Relational Representations with Auto-encoding Logic Programs
    Sebastijan DumancicTias GunsWannes Meert, and Hendrik Blockeel
    In International Joint Conference on Artificial Intelligence, 2019
  2. A comparative study of distributional and symbolic paradigms for relational learning
    Sebastijan Dumancic, Alberto Garcı́a-Durán, and Mathias Niepert
    In International Joint Conference on Artificial Intelligence, 2019

2018

  1. On embeddings as an alternative paradigm for relational learning
    Sebastijan Dumancic, Alberto Garcı́a-Durán, and Mathias Niepert
    In 8th workshop on Statistical Relational Artificial Intelligence StarAI at IJCAI/ICML, 2018
  2. Auto-encoding Logic Programs
    Sebastijan DumancicTias GunsWannes Meert, and Hendrik Blockeel
    In 2nd workshop on Neural Abstract Machines and Program Induction NAMPI at ICML, 2018
  3. COBRAS: Fast, Iterative, Active Clustering with Pairwise Constraints
    Toon van CraenendonckSebastijan Dumancic, Elia Van Wolputte, and Hendrik Blockeel
    In Symposium on Intelligent Data Analysis (IDA) 2018, 2018
  4. COBRAS-TS: A new approach to Semi-Supervised Clustering of Time Series
    Toon van CraenendonckWannes MeertSebastijan Dumancic, and Hendrik Blockeel
    In Discovery Science, 2018
  5. DeepProbLog: Neural Probabilistic Logic Programming
    Robin Manhaeve, Sebastijan DumancicAngelika KimmigThomas Demeester, and Luc De Raedt
    In Advances in Neural Information Processing Systems (NIPS), 2018
  6. Learning Sequence Encoders for Temporal Knowledge Graph Completion
    Alberto Garcı́a-Durán, Sebastijan Dumancic, and Mathias Niepert
    In Empirical Methods in Natural Language Processing, 2018

2017

  1. Demystifying Relational Latent Representations
    Sebastijan Dumancic, and Hendrik Blockeel
    In ILP, 2017
  2. Clustering-Based Relational Unsupervised Representation Learning with an Explicit Distributed Representation
    Sebastijan Dumancic, and Hendrik Blockeel
    In IJCAI, 2017
  3. COBRA: A Fast and Simple Method for Active Clustering with Pairwise Constraints
    Toon van CraenendonckSebastijan Dumancic, and Hendrik Blockeel
    In IJCAI, 2017
  4. An expressive dissimilarity measure for relational clustering using neighbourhood trees
    Sebastijan Dumancic, and Hendrik Blockeel
    Machine Learning, 2017

2016

  1. Unsupervised Relational Representation Learning via Clustering: Preliminary Results
    Sebastijan Dumancic, and Hendrik Blockeel
    In 6th workshop on Statistical Relational Artificial Intelligence StarAI at IJCAI, 2016
  2. Theory reconstruction: a representation learning view on predicate invention
    Sebastijan DumancicWannes Meert, and Hendrik Blockeel
    In 6th workshop on Statistical Relational Artificial Intelligence StarAI at IJCAI, 2016

2015

    2014