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Cesare Alippi

19 papers · 2016–2026 · 6 venues · across top CS/AI venues

Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.

Achievements

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+7 more ↓ πŸ—ΊοΈ Taxonomy Completionist (27) 🌍 Conference Polyglot Β· Silver πŸƒ Academic Marathon Β· Half πŸŒ‰ Interdisciplinary Bridge Β· Gold 🐣 Hot Topic Early Bird
πŸ”¬ Deep Specialist (15) πŸ† Grand Slam 🧬 Topic Evolution πŸ”₯ Unstoppable Β· Bronze 🌈 Renaissance Researcher (6) πŸ—ƒοΈ Keyword Collector (89) πŸ’Ž Century Club Β· Bronze

Venues

ICML (6) NeurIPS (4) ICLR (3) AAAI (2) IJCAI (2) JMLR (2)

Top co-authors

Andrea Cini (9) Daniele Zambon (8) Ivan Marisca (5) Filippo Maria Bianchi (4) Daniele Grattarola (3) Danilo Mandic (2) Lorenzo Livi (2) Giacomo Boracchi (1) Marcello Restelli (1) Alessio Gravina (1)

Research topics

Deep Learning (16) Architectures (16) Machine Learning (15) Core Methods (9) Optimization & Theory (6) Data Science & Analytics (5) Methods (5) Artificial Intelligence (2) Application Areas (2) Core AI (2) Learning Types Β· Machine Learning (2) Learning Types Β· Deep Learning (2) Computer Science (1) Knowledge & Reasoning (1) Mathematics & Optimization (1)

Keywords

graph neural network (11) spatiotemporal forecasting (3) node embedding (3) attention mechanism (2) spatio-temporal graph (2) message passing (2) time series (2) temporal dynamics (1) spectral clustering (1) temporal difference learning (1) graph representation learning (1) knowledge distillation (1) class-incremental learning (1) graph representation (1) graph learning (1) conformal prediction (1) time series prediction (1) function approximation (1) community detection (1) graph structure (1)

Papers

Compensating Distribution Drifts in Continual Learning with Pre-trained Vision Transformers AAAI 2026 Learning Latent Graph Structures and their Uncertainty ICML 2025 Relational Conformal Prediction for Correlated Time Series ICML 2025 Graph-based Forecasting with Missing Data through Spatiotemporal Downsampling ICML 2024 Graph-based Time Series Clustering for End-to-End Hierarchical Forecasting ICML 2024 Graph-based Virtual Sensing from Sparse and Partial Multivariate Observations ICLR 2024 Temporal Graph ODEs for Irregularly-Sampled Time Series IJCAI 2024 Scalable Spatiotemporal Graph Neural Networks AAAI 2023 Sparse Graph Learning from Spatiotemporal Time Series JMLR 2023 Taming Local Effects in Graph-based Spatiotemporal Forecasting NeurIPS 2023 AZ-whiteness test: a test for signal uncorrelation on spatio-temporal graphs NeurIPS 2022 Filling the G_ap_s: Multivariate Time Series Imputation by Graph Neural Networks ICLR 2022 Learning to Reconstruct Missing Data from Spatiotemporal Graphs with Sparse Observations NeurIPS 2022 Gaussian Approximation for Bias Reduction in Q-Learning JMLR 2021 Graph Edit Networks ICLR 2021 Learning Graph Cellular Automata NeurIPS 2021 Graph Random Neural Features for Distance-Preserving Graph Representations ICML 2020 Spectral Clustering with Graph Neural Networks for Graph Pooling ICML 2020 Change Detection in Multivariate Datastreams: Likelihood and Detectability Loss IJCAI 2016