Enhancing resilience of interdependent networks by healing. - Marcell Stippinger; János Kertész (CoRR, 2013)

Universality and scaling laws in interdependent networks: The healing model and the case of finite range interdependency. - Marcell Stippinger; János Kertész (CoRR, 2017)

Relaxation of Some Confusions about Confounders. - Ádám Zlatniczki; Marcell Stippinger; Zsigmond Benko; Zoltán Somogyvári; András Telcs (Entropy, 2021)

Manifold-adaptive dimension estimation revisited. - Zsigmond Benko; Marcell Stippinger; Roberta Rehus; Attila Bencze; Dániel Fabó; Boglárka Hajnal; Loránd G. Eröss; András Telcs; Zoltán Somogyvári (PeerJ Comput. Sci., 2022)

BiometricBlender: Ultra-high dimensional, multi-class synthetic data generator to imitate biometric feature space. - Marcell Stippinger; Dávid Hanák; Marcell T. Kurbucz; Gergely Hanczár; Olivér M. Törteli; Zoltán Somogyvári (SoftwareX, 2023)

Feature space reduction method for ultrahigh-dimensional, multiclass data: random forest-based multiround screening (RFMS). - Gergely Hanczár; Marcell Stippinger; Dávid Hanák; Marcell T. Kurbucz; Olivér M. Törteli; Ágnes Chripkó; Zoltán Somogyvári (Mach. Learn. Sci. Technol., 2023)

Detecting Causality in the Frequency Domain with Cross-Mapping Coherence. - Zsigmond Benko; Bálint Varga; Marcell Stippinger; Zoltán Somogyvári (CoRR, 2024)

Inference of hidden common driver dynamics by anisotropic self-organizing neural networks. - Zsigmond Benko; Marcell Stippinger; Zoltán Somogyvári (CoRR, 2025)