Time Series Forecasting Models Copy the Past: How to Mitigate. - Chrysoula Kosma; Giannis Nikolentzos; Nancy Xu; Michalis Vazirgiannis (ICANN (1), 2022)

TimeGNN: Temporal Dynamic Graph Learning for Time Series Forecasting. - Nancy Xu; Chrysoula Kosma; Michalis Vazirgiannis (COMPLEX NETWORKS (1), 2023)

Time-Parameterized Convolutional Neural Networks for Irregularly Sampled Time Series. - Chrysoula Kosma; Giannis Nikolentzos; Michalis Vazirgiannis (CoRR, 2023)

Neural Ordinary Differential Equations for Modeling Epidemic Spreading. - Chrysoula Kosma; Giannis Nikolentzos; George Panagopoulos; Jean-Marc Steyaert; Michalis Vazirgiannis (Trans. Mach. Learn. Res., 2023)

Towards Robust Deep Learning Methods for Time Series Data and their Applications. (Vers des Méthodes Robustes d'Apprentissage Profond pour les Données de Séries Temporelles et leurs Applications). - Chrysoula Kosma (2023)

Signed Graph Autoencoder for Explainable and Polarization-Aware Network Embeddings. - Nikolaos Nakis; Chrysoula Kosma; Giannis Nikolentzos; Michail Chatzianastasis; Iakovos Evdaimon; Michalis Vazirgiannis (AISTATS, 2025)

The Signed Two-Space Proximity Model for Learning Representations in Protein-Protein Interaction Networks. - Nikolaos Nakis; Chrysoula Kosma; Anastasia Brativnyk; Michail Chatzianastasis; Iakovos Evdaimon; Michalis Vazirgiannis (CoRR, 2025)