Bacciu, Davide

42 publications

TMLR 2026 Learning and Transferring Physical Models Through Derivatives Alessandro Trenta, Andrea Cossu, Davide Bacciu

NeurIPS 2025 Deferring Concept Bottleneck Models: Learning to Defer Interventions to Inaccurate Experts Andrea Pugnana, Riccardo Massidda, Francesco Giannini, Pietro Barbiero, Mateo Espinosa Zarlenga, Roberto Pellungrini, Gabriele Dominici, Fosca Giannotti, Davide Bacciu

ICML 2025 Graph Adaptive Autoregressive Moving Average Models Moshe Eliasof, Alessio Gravina, Andrea Ceni, Claudio Gallicchio, Davide Bacciu, Carola-Bibiane Schönlieb

NeurIPS 2025 Graph Diffusion That Can Insert and Delete Matteo Ninniri, Marco Podda, Davide Bacciu

AAAI 2025 On Oversquashing in Graph Neural Networks Through the Lens of Dynamical Systems Alessio Gravina, Moshe Eliasof, Claudio Gallicchio, Davide Bacciu, Carola-Bibiane Schönlieb

ICLR 2025 Port-Hamiltonian Architectural Bias for Long-Range Propagation in Deep Graph Networks Simon Heilig, Alessio Gravina, Alessandro Trenta, Claudio Gallicchio, Davide Bacciu

NeurIPS 2025 Return of ChebNet: Understanding and Improving an Overlooked GNN on Long Range Tasks Ali Hariri, Alvaro Arroyo, Alessio Gravina, Moshe Eliasof, Carola-Bibiane Schönlieb, Davide Bacciu, Xiaowen Dong, Kamyar Azizzadenesheli, Pierre Vandergheynst

NeurIPS 2025 SONAR: Long-Range Graph Propagation Through Information Waves Alessandro Trenta, Alessio Gravina, Davide Bacciu

CVPRW 2024 Calibration of Continual Learning Models Lanpei Li, Elia Piccoli, Andrea Cossu, Davide Bacciu, Vincenzo Lomonaco

ECML-PKDD 2024 Classifier-Free Graph Diffusion for Molecular Property Targeting Matteo Ninniri, Marco Podda, Davide Bacciu

ICLR 2024 Constraint-Free Structure Learning with Smooth Acyclic Orientations Riccardo Massidda, Francesco Landolfi, Martina Cinquini, Davide Bacciu

ICMLW 2024 Generalizing Convolution to Point Clouds Davide Bacciu, Francesco Landolfi

UAI 2024 Learning Causal Abstractions of Linear Structural Causal Models Riccardo Massidda, Sara Magliacane, Davide Bacciu

ICML 2024 Long Range Propagation on Continuous-Time Dynamic Graphs Alessio Gravina, Giulio Lovisotto, Claudio Gallicchio, Davide Bacciu, Claas Grohnfeldt

ICLRW 2024 MultiSTOP: Solving Functional Equations with Reinforcement Learning Alessandro Trenta, Davide Bacciu, Andrea Cossu, Pietro Ferrero

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

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

ICLR 2023 Anti-Symmetric DGN: A Stable Architecture for Deep Graph Networks Alessio Gravina, Davide Bacciu, Claudio Gallicchio

CLeaR 2023 Causal Abstraction with Soft Interventions Riccardo Massidda, Atticus Geiger, Thomas Icard, Davide Bacciu

CoLLAs 2023 Class-Incremental Learning with Repetition Hamed Hemati, Andrea Cossu, Antonio Carta, Julio Hurtado, Lorenzo Pellegrini, Davide Bacciu, Vincenzo Lomonaco, Damian Borth

ICMLW 2023 Decentralized Plasticity in Reservoir Dynamical Networks for Pervasive Environments Valerio De Caro, Davide Bacciu, Claudio Gallicchio

ICMLW 2023 Differentiable Causal Discovery with Smooth Acyclic Orientations Riccardo Massidda, Francesco Landolfi, Martina Cinquini, Davide Bacciu

ICLR 2023 Dual Algorithmic Reasoning Danilo Numeroso, Davide Bacciu, Petar Veličković

NeurIPSW 2023 Effective Non-Dissipative Propagation for Continuous-Time Dynamic Graphs Alessio Gravina, Giulio Lovisotto, Claudio Gallicchio, Davide Bacciu, Claas Grohnfeldt

AAAI 2023 Generalizing Downsampling from Regular Data to Graphs Davide Bacciu, Alessio Conte, Francesco Landolfi

IJCAI 2023 Graph-Based Polyphonic Multitrack Music Generation Emanuele Cosenza, Andrea Valenti, Davide Bacciu

ICCVW 2023 Memory Population in Continual Learning via Outlier Elimination Julio Hurtado, Alain Raymond-Saez, Vladimir Araujo, Vincenzo Lomonaco, Alvaro Soto, Davide Bacciu

LoG 2023 Neural Algorithmic Reasoning for Combinatorial Optimisation Dobrik Georgiev Georgiev, Danilo Numeroso, Davide Bacciu, Pietro Lio

CoLLAs 2023 Partial Hypernetworks for Continual Learning Hamed Hemati, Vincenzo Lomonaco, Davide Bacciu, Damian Borth

ICMLW 2023 Randomly Coupled Oscillators for Time Series Processing Andrea Ceni, Andrea Cossu, Jingyue Liu, Maximilian Stölzle, Cosimo Della Santina, Claudio Gallicchio, Davide Bacciu

CVPRW 2022 Ex-Model: Continual Learning from a Stream of Trained Models Antonio Carta, Andrea Cossu, Vincenzo Lomonaco, Davide Bacciu

ECML-PKDD 2022 Knowledge-Driven Interpretation of Convolutional Neural Networks Riccardo Massidda, Davide Bacciu

ICML 2022 The Infinite Contextual Graph Markov Model Daniele Castellana, Federico Errica, Davide Bacciu, Alessio Micheli

CVPRW 2021 Avalanche: An End-to-End Library for Continual Learning Vincenzo Lomonaco, Lorenzo Pellegrini, Andrea Cossu, Antonio Carta, Gabriele Graffieti, Tyler L. Hayes, Matthias De Lange, Marc Masana, Jary Pomponi, Gido M. van de Ven, Martin Mundt, Qi She, Keiland W. Cooper, Jeremy Forest, Eden Belouadah, Simone Calderara, German Ignacio Parisi, Fabio Cuzzolin, Andreas S. Tolias, Simone Scardapane, Luca Antiga, Subutai Ahmad, Adrian Popescu, Christopher Kanan, Joost van de Weijer, Tinne Tuytelaars, Davide Bacciu, Davide Maltoni

ICML 2021 Graph Mixture Density Networks Federico Errica, Davide Bacciu, Alessio Micheli

AISTATS 2020 A Deep Generative Model for Fragment-Based Molecule Generation Marco Podda, Davide Bacciu, Alessio Micheli

ICLR 2020 A Fair Comparison of Graph Neural Networks for Graph Classification Federico Errica, Marco Podda, Davide Bacciu, Alessio Micheli

NeurIPSW 2020 Generative Tomography Reconstruction Matteo Ronchetti, Davide Bacciu

ECML-PKDD 2020 Incremental Training of a Recurrent Neural Network Exploiting a Multi-Scale Dynamic Memory Antonio Carta, Alessandro Sperduti, Davide Bacciu

NeurIPSW 2020 K-Plex Cover Pooling for Graph Neural Networks Davide Bacciu, Alessio Conte, Roberto Grossi, Francesco Landolfi, Andrea Marino

MLOSS 2020 Probabilistic Learning on Graphs via Contextual Architectures Davide Bacciu, Federico Errica, Alessio Micheli

ICML 2018 Contextual Graph Markov Model: A Deep and Generative Approach to Graph Processing Davide Bacciu, Federico Errica, Alessio Micheli