1. Partial counterfactual identification and uplift modeling: theoretical results and real-world assessment

   • Théo Verhelst
   • Denis Mercier
   • Gianluca Bontempi

   OriginalPaper 14 March 2023 Pages: 1043 - 1067

   

2. Improving fraud detection via imbalanced graph structure learning

   • Lingfei Ren
   • Ruimin Hu
   • Wenyi Hu

   OriginalPaper 29 November 2023 Pages: 1069 - 1090

   

3. Composition of relational features with an application to explaining black-box predictors

   • Ashwin Srinivasan
   • A. Baskar
   • Devanshu Shah

   OriginalPaper 26 October 2023 Pages: 1091 - 1132

   

4. Differentially private Riemannian optimization

   • Andi Han
   • Bamdev Mishra
   • Junbin Gao

   OriginalPaper Open access 01 February 2024 Pages: 1133 - 1161

   

5. No regret sample selection with noisy labels

   • Heon Song
   • Nariaki Mitsuo
   • Daiki Suehiro

   OriginalPaper 05 January 2024 Pages: 1163 - 1188

   

6. On the effects of biased quantum random numbers on the initialization of artificial neural networks

   • Raoul Heese
   • Moritz Wolter
   • Nico Piatkowski

   OriginalPaper Open access 16 January 2024 Pages: 1189 - 1217

   

7. Utilising energy function and variational inference training for learning a graph neural network architecture

   • Gayathri Girish
   • Deepak Mishra
   • Subrahamanian K. S. Moosath

   OriginalPaper 23 January 2024 Pages: 1219 - 1241

   

8. OT-net: a reusable neural optimal transport solver

   • Zezeng Li
   • Shenghao Li
   • Zhongxuan Luo

   OriginalPaper 16 January 2024 Pages: 1243 - 1268

   

9. Word embeddings-based transfer learning for boosted relational dependency networks

   • Thais Luca
   • Aline Paes
   • Gerson Zaverucha

   OriginalPaper 20 September 2023 Pages: 1269 - 1302

   

10. Explainable models via compression of tree ensembles

    • Siwen Yan
    • Sriraam Natarajan
    • Prasad Tadepalli

    OriginalPaper 29 November 2023 Pages: 1303 - 1328

    

11. Structural causal models reveal confounder bias in linear program modelling

    • Matej Zečević
    • Devendra Singh Dhami
    • Kristian Kersting

    OriginalPaper Open access 09 January 2024 Pages: 1329 - 1349

    

12. Modeling PU learning using probabilistic logic programming

    • Victor Verreet
    • Luc De Raedt
    • Jessa Bekker

    OriginalPaper 27 November 2023 Pages: 1351 - 1372

    

13. Persistence B-spline grids: stable vector representation of persistence diagrams based on data fitting

    • Zhetong Dong
    • Hongwei Lin
    • Gengchen Li

    OriginalPaper 03 January 2024 Pages: 1373 - 1420

    

14. Principled diverse counterfactuals in multilinear models

    • Ioannis Papantonis
    • Vaishak Belle

    OriginalPaper Open access 10 January 2024 Pages: 1421 - 1443

    

15. Online semi-supervised learning of composite event rules by combining structure and mass-based predicate similarity

    • Evangelos Michelioudakis
    • Alexander Artikis
    • Georgios Paliouras

    OriginalPaper Open access 15 December 2023 Pages: 1445 - 1481

    

16. Fast deep mixtures of Gaussian process experts

    • Clement Etienam
    • Kody J. H. Law
    • Vitaly Zankin

    OriginalPaper Open access 08 January 2024 Pages: 1483 - 1508

    

17. Correction to: Learning to bid and rank together in recommendation systems

    • Geng Ji
    • Wentao Jiang
    • Zheqing Zhu

    Correction Open access 04 January 2024 Pages: 1509 - 1509