ECG Monitoring in Wearable Devices by Sparse Models. - Diego Carrera; Beatrice Rossi; Daniele Zambon; Pasqualina Fragneto; Giacomo Boracchi (ECML/PKDD (3), 2016)

Detecting changes in sequences of attributed graphs. - Daniele Zambon; Lorenzo Livi; Cesare Alippi (SSCI, 2017)

Anomaly and Change Detection in Graph Streams through Constant-Curvature Manifold Embeddings. - Daniele Zambon; Lorenzo Livi; Cesare Alippi (IJCNN, 2018)

Learning Graph Embeddings on Constant-Curvature Manifolds for Change Detection in Graph Streams. - Daniele Grattarola; Daniele Zambon; Cesare Alippi; Lorenzo Livi (CoRR, 2018)

Concept Drift and Anomaly Detection in Graph Streams. - Daniele Zambon; Cesare Alippi; Lorenzo Livi (IEEE Trans. Neural Networks Learn. Syst., 2018)

Autoregressive Models for Sequences of Graphs. - Daniele Zambon; Daniele Grattarola; Lorenzo Livi; Cesare Alippi (IJCNN, 2019)

Distance-Preserving Graph Embeddings from Random Neural Features. - Daniele Zambon; Cesare Alippi; Lorenzo Livi (CoRR, 2019)

Change-Point Methods on a Sequence of Graphs. - Daniele Zambon; Cesare Alippi; Lorenzo Livi (IEEE Trans. Signal Process., 2019)

Graph Random Neural Features for Distance-Preserving Graph Representations. - Daniele Zambon; Cesare Alippi; Lorenzo Livi (ICML, 2020)

Change Detection in Graph Streams by Learning Graph Embeddings on Constant-Curvature Manifolds. - Daniele Grattarola; Daniele Zambon; Lorenzo Livi; Cesare Alippi (IEEE Trans. Neural Networks Learn. Syst., 2020)

Graph Edit Networks. - Benjamin Paassen; Daniele Grattarola; Daniele Zambon; Cesare Alippi; Barbara Hammer (ICLR, 2021)

Erkennung von Anomalien und Veränderung in Graphsequenzen. - Daniele Zambon (Ausgezeichnete Informatikdissertationen, 2021)

Deep Learning for Graphs. - Davide Bacciu; Federico Errica; Nicolò Navarin; Luca Pasa; Daniele Zambon (ESANN, 2022)

Understanding Catastrophic Forgetting of Gated Linear Networks in Continual Learning. - Matteo Munari; Luca Pasa; Daniele Zambon; Cesare Alippi; Nicolò Navarin (IJCNN, 2022)

Graph iForest: Isolation of anomalous and outlier graphs. - Daniele Zambon; Lorenzo Livi; Cesare Alippi (IJCNN, 2022)

AZ-whiteness test: a test for signal uncorrelation on spatio-temporal graphs. - Daniele Zambon; Cesare Alippi (NeurIPS, 2022)

AZ-whiteness test: a test for uncorrelated noise on spatio-temporal graphs. - Daniele Zambon; Cesare Alippi (CoRR, 2022)

Sparse Graph Learning for Spatiotemporal Time Series. - Andrea Cini; Daniele Zambon; Cesare Alippi (CoRR, 2022)

Graph Representation Learning. - Davide Bacciu; Federico Errica; Alessio Micheli; Nicolò Navarin; Luca Pasa; Marco Podda; Daniele Zambon (ESANN, 2023)

Taming Local Effects in Graph-based Spatiotemporal Forecasting. - Andrea Cini; Ivan Marisca; Daniele Zambon; Cesare Alippi (NeurIPS, 2023)

Graph state-space models. - Daniele Zambon; Andrea Cini; Lorenzo Livi; Cesare Alippi (CoRR, 2023)

Where and How to Improve Graph-based Spatio-temporal Predictors. - Daniele Zambon; Cesare Alippi (CoRR, 2023)

Graph Kalman Filters. - Cesare Alippi; Daniele Zambon (CoRR, 2023)

Graph Deep Learning for Time Series Forecasting. - Andrea Cini; Ivan Marisca; Daniele Zambon; Cesare Alippi (CoRR, 2023)

Sparse Graph Learning from Spatiotemporal Time Series. - Andrea Cini; Daniele Zambon; Cesare Alippi (J. Mach. Learn. Res., 2023)

Graph-based Virtual Sensing from Sparse and Partial Multivariate Observations. - Giovanni de Felice; Andrea Cini; Daniele Zambon; Vladimir V. Gusev; Cesare Alippi (ICLR, 2024)

Temporal Graph ODEs for Irregularly-Sampled Time Series. - Alessio Gravina; Daniele Zambon; Davide Bacciu; Cesare Alippi (IJCAI, 2024)

Learning Latent Graph Structures and their Uncertainty. - Alessandro Manenti; Daniele Zambon; Cesare Alippi (CoRR, 2024)

Understanding Pooling in Graph Neural Networks. - Daniele Grattarola; Daniele Zambon; Filippo Maria Bianchi; Cesare Alippi (IEEE Trans. Neural Networks Learn. Syst., 2024)

A Survey on Graph Neural Networks for Time Series: Forecasting, Classification, Imputation, and Anomaly Detection. - Ming Jin 005; Huan Yee Koh; Qingsong Wen; Daniele Zambon; Cesare Alippi; Geoffrey I. Webb; Irwin King; Shirui Pan (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

PeakWeather: MeteoSwiss Weather Station Measurements for Spatiotemporal Deep Learning. - Daniele Zambon; Michele Cattaneo; Ivan Marisca; Jonas Bhend; Daniele Nerini; Cesare Alippi (CoRR, 2025)