Orsolya Csiszár

22 papers B 1C 1Misc 1Journal 14Unranked 4
YearRankTypeTitle / Venue / Authors
2024 J jnl
Parametric Activation Functions for Neural Networks: A Tutorial Survey.
IEEE Access
Luca Sára Pusztaházi, György Eigner, Orsolya Csiszár
2023 J jnl
Bayesian logical neural networks for human-centered applications in medicine.
Frontiers Bioinform.
Juan G. Díaz Ochoa, Lukas Maier, Orsolya Csiszár
2023 J jnl
Uninorm-like parametric activation functions for human-understandable neural models.
Knowl. Based Syst.
Orsolya Csiszár, Luca Sára Pusztaházi, Lehel Dénes-Fazakas, Michael S. Gashler, Vladik Kreinovich, Gábor Csiszár
2023 — conf
Why Fuzzy Control Is Often More Robust (and Smoother): A Theoretical Explanation.
SSCI
Orsolya Csiszár, Gábor Csiszár, Olga Kosheleva, Martine Ceberio, Vladik Kreinovich
2022 Misc conf
Parametric activation functions modelling fuzzy connectives for better explainability of neural models.
SISY
Luca Sára Pusztaházi, Gábor Csiszár, Michael S. Gashler, Orsolya Csiszár
2022 J jnl
Uninorm-like parametric activation functions for human-understandable neural models.
CoRR
Orsolya Csiszár, Luca Sára Pusztaházi, Lehel Dénes-Fazakas, Michael S. Gashler, Vladik Kreinovich, Gábor Csiszár
2021 — book
Explainable Neural Networks Based on Fuzzy Logic and Multi-criteria Decision Tools
József Dombi, Orsolya Csiszár
2021 J jnl
Medical recommender systems based on continuous-valued logic and multi-criteria decision operators, using interpretable neural networks.
BMC Medical Informatics Decis. Mak.
Juan G. Díaz Ochoa, Orsolya Csiszár, Thomas Schimper
2021 J jnl
Squashing activation functions in benchmark tests: Towards a more eXplainable Artificial Intelligence using continuous-valued logic.
Knowl. Based Syst.
Daniel Zeltner, Benedikt Schmid, Gábor Csiszár, Orsolya Csiszár
2021 — conf
Why Kappa Regression?
IFSA/EUSFLAT/AGOP
Julio C. Urenda, Orsolya Csiszár, Gábor Csiszár, József Dombi, György Eigner, Olga Kosheleva, Vladik Kreinovich
2020 J jnl
How to implement MCDM tools and continuous logic into neural computation?: Towards better interpretability of neural networks.
Knowl. Based Syst.
Orsolya Csiszár, Gábor Csiszár, József Dombi
2020 J jnl
Interpretable neural networks based on continuous-valued logic and multicriteria decision operators.
Knowl. Based Syst.
Orsolya Csiszár, Gábor Csiszár, József Dombi
2020 — conf
Natural Invariance Explains Empirical Success of Specific Membership Functions, Hedge Operations, and Negation Operations.
NAFIPS
Julio C. Urenda, Orsolya Csiszár, Gábor Csiszár, József Dombi, György Eigner, Vladik Kreinovich
2020 J jnl
Squashing activation functions in benchmark tests: towards eXplainable Artificial Intelligence using continuous-valued logic.
CoRR
Daniel Zeltner, Benedikt Schmid, Gábor Csiszár, Orsolya Csiszár
2020 B conf
Why Squashing Functions in Multi-Layer Neural Networks.
SMC
Julio C. Urenda, Orsolya Csiszár, Gábor Csiszár, József Dombi, Olga Kosheleva, Vladik Kreinovich, György Eigner
2019 — conf
Generator-based Modifiers and Membership Functions in Nilpotent Operator Systems.
IWOBI
Orsolya Csiszár, József Dombi
2019 J jnl
Semantic Interpretation of Deep Neural Networks Based on Continuous Logic.
CoRR
József Dombi, Orsolya Csiszár, Gábor Csiszár
2018 C conf
Operator-dependent Modifiers in Nilpotent Logical Systems.
IJCCI
József Dombi, Orsolya Csiszár
2017 J jnl
Self-dual operators and a general framework for weighted nilpotent operators.
Int. J. Approx. Reason.
József Dombi, Orsolya Csiszár
2016 J jnl
Equivalence operators in nilpotent systems.
Fuzzy Sets Syst.
József Dombi, Orsolya Csiszár
2015 J jnl
The general nilpotent operator system.
Fuzzy Sets Syst.
József Dombi, Orsolya Csiszár
2014 J jnl
Implications in bounded systems.
Inf. Sci.
József Dombi, Orsolya Csiszár