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Vreeken, Jilles

  1. Formally Justifying MDL-based Inference of Cause and Effect
    2021/05/05 by Marx, Alexander, Vreeken, Jilles · 3 citations
    #FOS: Computer and information sciences #Information Theory (cs.IT)
  2. We Are Not Your Real Parents: Telling Causal from Confounded using MDL
    2019/01/21 by David Kaltenpoth, Kaltenpoth, David, Jilles Vreeken +1 · 2 citations
    Computer Science · #Bayesian Modeling and Causal Inference #Computability, Logic, AI Algorithms #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  3. Label-Descriptive Patterns and Their Application to Characterizing Classification Errors
    2021/10/18 by Hedderich, Michael, Fischer, Jonas, Klakow, Dietrich +1 · 2 citations
    #Computation and Language (cs.CL) #FOS: Computer and information sciences #Machine Learning (cs.LG)
  4. Causal Inference by Stochastic Complexity
    2017/02/22 by Kailash Budhathoki, Jilles Vreeken, Budhathoki, Kailash +1 · 2 citations
    Computer Science · Mathematics · #Bayesian Modeling and Causal Inference #Machine Learning and Algorithms #Statistical Methods and Inference
  5. VoG: Summarizing and Understanding Large Graphs
    2014/06/13 by Koutra, Danai, Kang, U, Vreeken, Jilles +1 · 1 citation
    #FOS: Computer and information sciences #FOS: Physical sciences #Physics and Society (physics.soc-ph) #Social and Information Networks (cs.SI)
  6. Generating Realistic Synthetic Population Datasets
    2016/02/22 by Wu, Hao, Ning, Yue, Chakraborty, Prithwish +3 · 1 citation
    #Databases (cs.DB) #FOS: Computer and information sciences
  7. Testing Conditional Independence on Discrete Data using Stochastic Complexity
    2019/03/12 by Marx, Alexander, Vreeken, Jilles · 1 citation
    #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  8. Efficiently Factorizing Boolean Matrices using Proximal Gradient Descent
    2023/07/14 by Dalleiger, Sebastian, Vreeken, Jilles · 1 citation
    #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  9. Learning Exceptional Subgroups by End-to-End Maximizing KL-divergence
    2024/02/20 by Sascha Xu, Nils Philipp Walter, Xu, Sascha +5 · 1 citation
    Computer Science · #FOS: Computer and information sciences #Face and Expression Recognition #Fuzzy Logic and Control Systems #Machine Learning (cs.LG) #Neural Networks and Applications
  10. Neuro-Symbolic Rule Lists
    2024/11/10 by Sascha Xu, Nils Philipp Walter, Xu, Sascha +3 · 1 citation
    Computer Science · #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Neural Networks and Applications
  11. From your Block to our Block: How to Find Shared Structure between Stochastic Block Models over Multiple Graphs
    2024/12/20 by Iiro Kumpulainen, Kumpulainen, Iiro, Sebastian Dalleiger +5 · 1 citation
    Physics and Astronomy · #Complex Network Analysis Techniques #FOS: Computer and information sciences #Social and Information Networks (cs.SI)
  12. SpaceTime: Causal Discovery from Non-Stationary Time Series
    2025/01/17 by Sarah Mameche, Mameche, Sarah, Lénaïg Cornanguer +5 · 1 citation
    Business, Management and Accounting · Computer Science · Decision Sciences · #Big Data and Business Intelligence #Data Quality and Management #FOS: Computer and information sciences #Geochemistry and Geologic Mapping #Machine Learning (cs.LG)