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Jilles Vreeken

Jilles Vreeken

D-Index & Metrics

Computer Science

D-Index
37
Citations
5785
World Ranking
10763
National Ranking
540

Overview

Jilles Vreeken is affiliated with the Max Planck Society in Germany and focuses primarily on research within the field of Computer Science, with a total of 112 publications. Their work extensively covers subfields such as Artificial Intelligence, Molecular Biology, Computational Theory and Mathematics, Management Science and Operations Research, and Computer Networks and Communications.

The scientist's research spans several main topics, including Bayesian Modeling and Causal Inference, Advanced Graph Neural Networks, Data Mining Algorithms and Applications, Rough Sets and Fuzzy Logic, Data Quality and Management, Advanced Database Systems and Queries, and Topic Modeling.

Vreeken has contributed to various publication venues across many years. Frequent venues include:

  • arXiv (Cornell University)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • OPAL (Open@LaTrobe) (La Trobe University)
  • Zenodo (CERN European Organization for Nuclear Research)
  • Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining

Recent publications from Jilles Vreeken include:

  • Identifying domains of applicability of machine learning models for materials science, 2020, Nature Communications
  • Integrative analysis of epigenetics data identifies gene-specific regulatory elements, 2021, Nucleic Acids Research
  • Data-driven equation for drug-membrane permeability across drugs and membranes, 2023, Wiardi Beckman Foundation
  • Discovering Significant Patterns under Sequential False Discovery Control, 2022, Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
  • Discovering dependencies with reliable mutual information, 2020, Knowledge and Information Systems

Collaborations have been a significant part of Vreeken's research endeavors, with frequent co-authors including:

  • Sebastian Dalleiger
  • Corinna Coupette
  • Dietrich Klakow
  • Mario Boley
  • Alexander Marx

Among book publications, Vreeken contributed to a volume published by the Society for Industrial and Applied Mathematics, specifically the Proceedings of the 2021 SIAM International Conference on Data Mining (SDM), which has received citations within the scientific community.

Best Publications

  • Krimp: mining itemsets that compress

    Jilles Vreeken;Matthijs Leeuwen;Arno Siebes

  • Spotting Culprits in Epidemics: How Many and Which Ones?

    B. Aditya Prakash;Jilles Vreeken;Christos Faloutsos

  • Intelligent Traffic Light Control

    Wiering;J. Veenen;J. Vreeken;A. Koopman

  • Item Sets that Compress.

    Arno Siebes;Jilles Vreeken;Matthijs van Leeuwen

  • Proceedings of the 2017 SIAM International Conference on Data Mining

    Nitesh Chawla;Wei Wang

  • Simulation and optimization of traffic in a city

    M. Wiering;J. Vreeken;J. van Veenen;A. Koopman

  • Spiking neural networks, an introduction

    J. Vreeken

  • Is exploratory search different? A comparison of information search behavior for exploratory and lookup tasks

    Kumaripaba Athukorala;Dorota Głowacka;Giulio Jacucci;Antti Oulasvirta

  • Fast and reliable anomaly detection in categorical data

    Leman Akoglu;Hanghang Tong;Jilles Vreeken;Christos Faloutsos

  • The long and the short of it: summarising event sequences with serial episodes

    Nikolaj Tatti;Jilles Vreeken

  • Tell me what i need to know: succinctly summarizing data with itemsets

    Michael Mampaey;Nikolaj Tatti;Jilles Vreeken

  • VoG: Summarizing and understanding large graphs

    Danai Koutra;U Kang;Jilles Vreeken;Christos Faloutsos

  • Identifying domains of applicability of machine learning models for materials science.

    Christopher A. Sutton;Mario Boley;Luca M. Ghiringhelli;Matthias Rupp;Matthias Rupp

  • Model order selection for boolean matrix factorization

    Pauli Miettinen;Jilles Vreeken

  • Summarizing and understanding large graphs

    Danai Koutra;U Kang;Jilles Vreeken;Christos Faloutsos

  • Efficiently spotting the starting points of an epidemic in a large graph

    B. Aditya Prakash;Jilles Vreeken;Christos Faloutsos

  • MDL4BMF: Minimum Description Length for Boolean Matrix Factorization

    Pauli Miettinen;Jilles Vreeken

  • Compression picks item sets that matter

    Matthijs van Leeuwen;Jilles Vreeken;Arno Siebes

  • The Odd One Out: Identifying and Characterising Anomalies

    Koen Smets;Jilles Vreeken

  • Slim: Directly Mining Descriptive Patterns.

    Koen Smets;Jilles Vreeken

Frequent Co-Authors

Christos Faloutsos
Christos Faloutsos Carnegie Mellon University
Gerhard Weikum
Gerhard Weikum Max Planck Institute for Informatics
Bart Goethals
Bart Goethals University of Antwerp
Duen Horng Chau
Duen Horng Chau Georgia Institute of Technology
Matthias Scheffler
Matthias Scheffler Fritz Haber Institute of the Max Planck Society
Leman Akoglu
Leman Akoglu Carnegie Mellon University
Danai Koutra
Danai Koutra University of Michigan–Ann Arbor
Hanghang Tong
Hanghang Tong University of Illinois at Urbana-Champaign
Naren Ramakrishnan
Naren Ramakrishnan Virginia Tech
Arthur Zimek
Arthur Zimek University of Southern Denmark

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