Interpreting RNN behaviour via excitable network attractors. - Andrea Ceni; Peter Ashwin; Lorenzo Livi (CoRR, 2018)

Interpreting Recurrent Neural Networks Behaviour via Excitable Network Attractors. - Andrea Ceni; Peter Ashwin; Lorenzo Livi (Cogn. Comput., 2020)

Interpreting multi-stable behaviour in input-driven recurrent neural networks - Andrea Ceni (2021)

Orthogonality in Additive Echo State Networks. - Andrea Ceni; Claudio Gallicchio (ESANN, 2022)

Improving Fairness via Intrinsic Plasticity in Echo State Networks. - Andrea Ceni; Davide Bacciu; Valerio De Caro; Claudio Gallicchio; Luca Oneto (ESANN, 2023)

Residual Reservoir Computing Neural Networks for Time-series Classification. - Claudio Gallicchio; Andrea Ceni (ESANN, 2023)

Edge of stability echo state networks. - Andrea Ceni; Claudio Gallicchio (CoRR, 2023)

Transitions in echo index and dependence on input repetitions. - Peter Ashwin; Andrea Ceni (CoRR, 2023)

Sparse Reservoir Topologies for Physical Implementations of Random Oscillators Networks. - Andrea Cossu; Andrea Ceni; Davide Bacciu; Claudio Gallicchio (AIMLSystems, 2024)

Random Oscillators Network for Time Series Processing. - Andrea Ceni; Andrea Cossu; Maximilian W. Stölzle; Jingyue Liu 001; Cosimo Della Santina; Davide Bacciu; Claudio Gallicchio (AISTATS, 2024)

EMERGE - Emergent Awareness from Minimal Collectives. - Davide Bacciu; Vincenzo Ambriola; Bahador Bahrami; Andrea Ceni; Andrea Cossu; Valerio De Caro; Cosimo Della Santina; Ophelia Deroy; Claudio Gallicchio; Riccardo Guidotti; Sabine Hauert; Simon Jones; et al. (ERF (1), 2024)

Reservoir Memory Networks. - Claudio Gallicchio; Andrea Ceni (ESANN, 2024)

Enhancing Echo State Networks with Gradient-based Explainability Methods. - Francesco Spinnato; Andrea Cossu; Riccardo Guidotti; Andrea Ceni; Claudio Gallicchio; Davide Bacciu (ESANN, 2024)

Non-dissipative Reservoir Computing Approaches for Time-Series Classification. - Claudio Gallicchio; Andrea Ceni (ICANN (10), 2024)

Continuously Deep Recurrent Neural Networks. - Andrea Ceni; Peter Ford Dominey; Claudio Gallicchio; Alessio Micheli; Luca Pedrelli; Domenico Tortorella (ECML/PKDD (7), 2024)

Residual Echo State Networks: Residual recurrent neural networks with stable dynamics and fast learning. - Andrea Ceni; Claudio Gallicchio (Neurocomputing, 2024)

GRAMA: Adaptive Graph Autoregressive Moving Average Models. - Moshe Eliasof; Alessio Gravina; Andrea Ceni; Claudio Gallicchio; Davide Bacciu; Carola-Bibiane Schönlieb (CoRR, 2025)

Edge of Stability Echo State Network. - Andrea Ceni; Claudio Gallicchio (IEEE Trans. Neural Networks Learn. Syst., 2025)

Message-Passing State-Space Models: Improving Graph Learning with Modern Sequence Modeling. - Andrea Ceni; Alessio Gravina; Claudio Gallicchio; Davide Bacciu; Carola-Bibiane Schönlieb; Moshe Eliasof (CoRR, 2025)

Random Orthogonal Additive Filters: A Solution to the Vanishing/Exploding Gradient of Deep Neural Networks. - Andrea Ceni (IEEE Trans. Neural Networks Learn. Syst., 2025)

Residual Reservoir Memory Networks. - Matteo Pinna; Andrea Ceni; Claudio Gallicchio (CoRR, 2025)