ReSeg: A Recurrent Neural Network-Based Model for Semantic Segmentation. - Francesco Visin; Adriana Romero; Kyunghyun Cho; Matteo Matteucci; Marco Ciccone; Kyle Kastner; Yoshua Bengio; Aaron C. Courville (CVPR Workshops, 2016)

Multi-view Stereo with Single-View Semantic Mesh Refinement. - Andrea Romanoni; Marco Ciccone; Francesco Visin; Matteo Matteucci (ICCV Workshops, 2017)

NAIS-Net: Stable Deep Networks from Non-Autonomous Differential Equations. - Marco Ciccone; Marco Gallieri; Jonathan Masci; Christian Osendorfer; Faustino J. Gomez (NeurIPS, 2018)

Event-based Convolutional Networks for Object Detection in Neuromorphic Cameras. - Marco Cannici; Marco Ciccone; Andrea Romanoni; Matteo Matteucci (CoRR, 2018)

ReConvNet: Video Object Segmentation with Spatio-Temporal Features Modulation. - Francesco Lattari; Marco Ciccone; Matteo Matteucci; Jonathan Masci; Francesco Visin (CoRR, 2018)

Asynchronous Convolutional Networks for Object Detection in Neuromorphic Cameras. - Marco Cannici; Marco Ciccone; Andrea Romanoni; Matteo Matteucci (CVPR Workshops, 2019)

Attention Mechanisms for Object Recognition With Event-Based Cameras. - Marco Cannici; Marco Ciccone; Andrea Romanoni; Matteo Matteucci (WACV, 2019)

Coordination in Adversarial Sequential Team Games via Multi-Agent Deep Reinforcement Learning. - Andrea Celli; Marco Ciccone; Raffaele Bongo; Nicola Gatti 001 (CoRR, 2019)

A Differentiable Recurrent Surface for Asynchronous Event-Based Data. - Marco Cannici; Marco Ciccone; Andrea Romanoni; Matteo Matteucci (ECCV (20), 2020)

Matrix-LSTM: a Differentiable Recurrent Surface for Asynchronous Event-Based Data. - Marco Cannici; Marco Ciccone; Andrea Romanoni; Matteo Matteucci (CoRR, 2020)

Multi-Agent Coordination in Adversarial Environments through Signal Mediated Strategies. - Federico Cacciamani; Andrea Celli; Marco Ciccone; Nicola Gatti 001 (AAMAS, 2021)

Cluster-Driven Graph Federated Learning Over Multiple Domains. - Debora Caldarola; Massimiliano Mancini; Fabio Galasso; Marco Ciccone; Emanuele Rodolà; Barbara Caputo (CVPR Workshops, 2021)

N-ROD: A Neuromorphic Dataset for Synthetic-to-Real Domain Adaptation. - Marco Cannici; Chiara Plizzari; Mirco Planamente; Marco Ciccone; Andrea Bottino; Barbara Caputo; Matteo Matteucci (CVPR Workshops, 2021)

NeurIPS 2022 Competition Track Revised Selected Papers. - Marco Ciccone; Gustavo Stolovitzky; Jacob Albrecht (NeurIPS (Competition and Demos), 2021)

DA4Event: Towards Bridging the Sim-to-Real Gap for Event Cameras Using Domain Adaptation. - Mirco Planamente; Chiara Plizzari; Marco Cannici; Marco Ciccone; Francesco Strada; Andrea Bottino; Matteo Matteucci; Barbara Caputo (IEEE Robotics Autom. Lett., 2021)

On iterative and conditional computation for visual representation learning. - Marco Ciccone (2021)

Incremental Learning in Semantic Segmentation from Image Labels. - Fabio Cermelli; Dario Fontanel; Antonio Tavera; Marco Ciccone; Barbara Caputo (CVPR, 2022)

Improving Generalization in Federated Learning by Seeking Flat Minima. - Debora Caldarola; Barbara Caputo; Marco Ciccone (ECCV (23), 2022)

A Marriage between Adversarial Team Games and 2-player Games: Enabling Abstractions, No-regret Learning, and Subgame Solving. - Luca Carminati; Federico Cacciamani; Marco Ciccone; Nicola Gatti 001 (ICML, 2022)

Speeding up Heterogeneous Federated Learning with Sequentially Trained Superclients. - Riccardo Zaccone; Andrea Rizzardi; Debora Caldarola; Marco Ciccone; Barbara Caputo (ICPR, 2022)

Transient-Fault-Aware Design and Training to Enhance DNNs Reliability with Zero-Overhead. - Niccolò Cavagnero; Fernando Fernandes dos Santos; Marco Ciccone; Giuseppe Averta; Tatiana Tommasi; Paolo Rech (IOLTS, 2022)

FedDrive: Generalizing Federated Learning to Semantic Segmentation in Autonomous Driving. - Lidia Fantauzzo; Eros Fanì; Debora Caldarola; Antonio Tavera; Fabio Cermelli; Marco Ciccone; Barbara Caputo (IROS, 2022)

Public Information Representation for Adversarial Team Games. - Luca Carminati; Federico Cacciamani; Marco Ciccone; Nicola Gatti 001 (CoRR, 2022)

Fault-Aware Design and Training to Enhance DNNs Reliability with Zero-Overhead. - Niccolò Cavagnero; Fernando Fernandes dos Santos; Marco Ciccone; Giuseppe Averta; Tatiana Tommasi; Paolo Rech (CoRR, 2022)

Schedule-Robust Online Continual Learning. - Ruohan Wang; Marco Ciccone; Giulia Luise; Andrew Yapp; Massimiliano Pontil; Carlo Ciliberto (CoRR, 2022)

Window-based Model Averaging Improves Generalization in Heterogeneous Federated Learning. - Debora Caldarola; Barbara Caputo; Marco Ciccone (ICCV (Workshops), 2023)

From charts to atlas: Merging latent spaces into one. - Donato Crisostomi; Irene Cannistraci; Luca Moschella; Pietro Barbiero; Marco Ciccone; Pietro Liò; Emanuele Rodolà (NeurReps, 2023)

Learning Across Domains and Devices: Style-Driven Source-Free Domain Adaptation in Clustered Federated Learning. - Donald Shenaj; Eros Fanì; Marco Toldo; Debora Caldarola; Antonio Tavera; Umberto Michieli; Marco Ciccone; Pietro Zanuttigh; Barbara Caputo (WACV, 2023)

FedDrive v2: an Analysis of the Impact of Label Skewness in Federated Semantic Segmentation for Autonomous Driving. - Eros Fanì; Marco Ciccone; Barbara Caputo (CoRR, 2023)

Communication-Efficient Heterogeneous Federated Learning with Generalized Heavy-Ball Momentum. - Riccardo Zaccone; Carlo Masone; Marco Ciccone (CoRR, 2023)

PEM: Prototype-Based Efficient MaskFormer for Image Segmentation. - Niccolò Cavagnero; Gabriele Rosi; Claudia Cuttano; Francesca Pistilli; Marco Ciccone; Giuseppe Averta; Fabio Cermelli (CVPR, 2024)

Finding Lottery Tickets in Vision Models via Data-Driven Spectral Foresight Pruning. - Leonardo Iurada; Marco Ciccone; Tatiana Tommasi (CVPR, 2024)

Accelerating Heterogeneous Federated Learning with Closed-form Classifiers. - Eros Fanì; Raffaello Camoriano; Barbara Caputo; Marco Ciccone (ICML, 2024)

Accelerating Federated Learning via Sequential Training of Grouped Heterogeneous Clients. - Andrea Silvi; Andrea Rizzardi; Debora Caldarola; Barbara Caputo; Marco Ciccone (IEEE Access, 2024)

Beyond Local Sharpness: Communication-Efficient Global Sharpness-aware Minimization for Federated Learning. - Debora Caldarola; Pietro Cagnasso; Barbara Caputo; Marco Ciccone (CVPR, 2025)

Efficient Model Editing with Task-Localized Sparse Fine-tuning. - Leonardo Iurada; Marco Ciccone; Tatiana Tommasi (ICLR, 2025)

Resource-Efficient Personalization in Federated Learning With Closed-Form Classifiers. - Eros Fanì; Raffaello Camoriano; Barbara Caputo; Marco Ciccone (IEEE Access, 2025)

Domain generalization using action sequences for egocentric action recognition. - Amirshayan Nasirimajd; Chiara Plizzari; Simone Alberto Peirone; Marco Ciccone; Giuseppe Averta; Barbara Caputo (Pattern Recognit. Lett., 2025)

Communication-Efficient Heterogeneous Federated Learning with Generalized Heavy-Ball Momentum. - Riccardo Zaccone; Sai Praneeth Karimireddy; Carlo Masone; Marco Ciccone (Trans. Mach. Learn. Res., 2025)

Interaction-Aware Gaussian Weighting for Clustered Federated Learning. - Alessandro Licciardi; Davide Leo; Eros Fanì; Barbara Caputo; Marco Ciccone (CoRR, 2025)