Unifying perspectives: plausible counterfactual explanations on global, group-wise, and local levels
O Furman, PE Wielopolski, ŁD Lenkiewicz, MM Zięba, J Stefanowski
IJCAI 2026
2026
Patryk Wielopolski
PhD Student
Research groups
Publications8
Multi-Label conditional generation from pre-trained models
MM Zięba, PE Wielopolski, M Proszewska, M Wołczyk, Ł Maziarka, M Śmieja
IEEE Transactions on Pattern Analysis and Machine Intelligence 46(9), 6185–6198 · Cited by 2
2024
Probabilistically plausible counterfactual explanations with normalizing flows
PE Wielopolski, O Furman, MM Zięba, J Stefanowski
13th Conference on Prestigious Applications of Intelligent Systems (PAIS 2024) 954–961 · Cited by 2
2024
NodeFlow: towards end-to-end flexible probabilistic regression on tabular data
PE Wielopolski, O Furman, MM Zięba
Entropy 26(7), 1–16 · Cited by 2
2024
Modeling uncertainty in personalized emotion prediction with normalizing flows
PD Miłkowski, K Karanowski, PE Wielopolski, J Kocoń, P Kazienko, MM Zięba
23nd IEEE International Conference on Data Mining Workshops (ICDMW), 1–4 December 2023 Shanghai, China 757–766
2023
Treeflow: going beyond tree-based parametric probabilistic regression
PE Wielopolski, MM Zięba
ECAI 2023 2631–2638 · Cited by 3
2023
Flow Plugin Network for conditional generation
PE Wielopolski, MM Zięba, M Koperski
ACIIDS 2023 221–232 · Cited by 2
2023
PluGeN: multi-label conditional generation from pre-trained models
MM Zięba, PE Wielopolski, M Wołczyk, M Proszewska, Ł Maziarka, R Kurczab, …
Proceedings of the 36th AAAI Conference on Artificial Intelligence 8647–8656 · Cited by 7
2022