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
Doktorant
Grupy badawcze
Publikacje8
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 · Cytowane przez 2
2024
Probabilistically plausible counterfactual explanations with normalizing flows
PE Wielopolski, O Furman, MM Zięba, J Stefanowski
Frontiers in artificial intelligence and applications · Cytowane przez 2
2024
NodeFlow: towards end-to-end flexible probabilistic regression on tabular data
PE Wielopolski, O Furman, MM Zięba
Entropy · Cytowane przez 2
2024
Modeling uncertainty in personalized emotion prediction with normalizing flows
PD Miłkowski, K Karanowski, PE Wielopolski, J Kocoń, P Kazienko, MM Zięba
IEEE International Conference on Data Mining Workshops, ICDMW
2023
Treeflow: going beyond tree-based parametric probabilistic regression
PE Wielopolski, MM Zięba
Frontiers in artificial intelligence and applications · Cytowane przez 3
2023
Flow Plugin Network for conditional generation
PE Wielopolski, MM Zięba, M Koperski
Lecture notes in computer science · Cytowane przez 2
2023
PluGeN: multi-label conditional generation from pre-trained models
MM Zięba, PE Wielopolski, M Wołczyk, M Proszewska, Ł Maziarka, R Kurczab, …
AAAI Press 8647–8656 · Cytowane przez 7
2022