Machine Learning & Computational Neuroscience

• D. Maltoni and M. Ferrara, Arithmetic with language models: From memorization to computation , Neural Networks, July 2024. Abstract
• V. Lomonaco, L. Pellegrini, G. Graffieti and D. Maltoni, Architect, Regularize and Replay: A Flexible Hybrid Approach for Continual Learning , in Towards Human Brain Inspired Lifelong Learning, World Scientific, 2024. Abstract
• L. Vorabbi, D. Maltoni and S. Santi, On-Device Learning with Binary Neural Networks , in proceedings International Conference on Image Analysis and Processing (ICIAP), January 2024. Abstract
• L. Vorabbi, D. Maltoni, G. Borghi and S. Santi, Enabling On-Device Continual Learning with Binary Neural Networks and Latent Replay , in proceedings 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISAPP), 2024. Abstract
• L. Vorabbi, D. Maltoni and S. Santi, Input Layer Binarization with Bit-Plane Encoding , in proceedings International Conference on Artificial Neural Networks, September 2023. Abstract
• G. Graffieti, D. Maltoni, L. Pellegrini and V. Lomonaco, Generative negative replay for continual learning , Neural Networks, May 2023. Abstract
• L. Pellegrini, D. Maltoni, G. Graffieti, V. Lomonaco, L. Mazzini, M. Mondardini and M. Zappoli, A weakly supervised approach for recycling code recognition , Expert Systems With Applications, April 2023. Abstract
• G. Graffieti, G. Borghi and D. Maltoni, Continual learning in real-life applications , IEEE Robotics and Automation Letters, July 2022. Abstract
• A. Cossu, G. Graffieti, L. Pellegrini, D. Maltoni, D. Bacciu, A. Carta and V. Lomonaco, Is class-incremental enough for continual learning? , Frontiers in Artificial Intelligence, March 2022. Abstract
• V. Lomonaco, L. Pellegrini, P. Rodriguez, M. Caccia, Q. She, Y. Chen, Q. Jodelet, R. Wang, Z. May, D. Vasquez, G.I. Parisi, N. Churamani, M. Pickett, I. Laradji and D. Maltoni, CVPR 2020 continual learning in computer vision competition: Approaches, results, current challenges and future directions , Artificial Intelligence, February 2022. Abstract
• V. Lomonaco, L. Pellegrini, A. Cossu, A. Carta, G. Graffieti, T.L. Hayes, M. De Lange, M. Masana, J. Pomponi, G.M. Van De Ven, M. Mundt, Q. She, K. Cooper, J. Forest, E. Belouadah, S. Calderara, G.I. Parisi, F. Cuzzolin, A.S. Tolias, S. Scardapane, L. Antiga, S. Ahmad, A. Popescu, C. Kanan, J. Van De Weijer, T. Tuytelaars, D. Bacciu and D. Maltoni, Avalanche: an End-to-End Library for Continual Learning , in proceedings Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), June 2021. Abstract
• L. Pellegrini, G. Graffieti, V. Lomonaco and D. Maltoni, Latent Replay for Real-Time Continual Learning , in proceedings International Conference on Intelligent Robots and Systems (IROS), October 2020. Abstract
• T. Lesort, V. Lomonaco, A. Stoian, D. Maltoni, D. Filliat and N. Díaz-Rodríguez, Continual learning for robotics: Definition, framework, learning strategies, opportunities and challenges , Information Fusion, vol.58, pp.52-68, June 2020. Abstract
• G. Graffieti, V. Lomonaco, D. Maltoni, L. Pellegrini and et al., IROS 2019 Lifelong Robotic Vision: Object Recognition Challenge , IEEE Robotics & Automation Magazine, February 2020.
• V. Lomonaco, K. Desai, E. Culurciello and D. Maltoni, Continual Reinforcement Learning in 3D Non-stationary Environments , in proceedings Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2020. Abstract
• L. Ravaglia, M. Rusci, A. Capotondi, F. Conti, L. Pellegrini, V. Lomonaco, D. Maltoni and L. Benini, Memory-latency-accuracy trade-offs for continual learning on a risc-v extreme-edge node , in proceedings Workshop on Signal Processing Systems (SiPS), 2020. Abstract
• V. Lomonaco, D. Maltoni and L. Pellegrini, Rehearsal-Free Continual Learning over Small Non-IID Batches , in proceedings Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2020. Abstract
• D. Maltoni and V. Lomonaco, Continuous learning in single-incremental-task scenarios , Neural Networks, August 2019. Abstract
• L. Mazzini, A. Franco and D. Maltoni, Gesture recognition by leap motion controller and LSTM networks for CAD-oriented interfaces , in proceedings International Conference on Image Analysis and Processing (ICIAP), undefined 2019. Abstract
• N. Díaz-Rodríguez, V. Lomonaco, D. Filliat and D. Maltoni, Don't Forget, There is More than Forgetting: new Metrics for Continual Learning , in proceedings Continual Learning Workshop at NeurIPS (NeurIPS2018), Montreal (Canada), December 2018. Abstract
• V. Lomonaco and D. Maltoni, CORe50: a New Dataset and Benchmark for Continuous Object Recognition , in proceedings Conference on Robot Learning (CoRL17), Mountain View (CA), pp.17-26, November 2017. Abstract
• D. Maltoni and V. Lomonaco, Semi-supervised Tuning from Temporal Coherence , in proceedings 23rd International Conference on Pattern Recognition (ICPR16), Cancun, Mexico, December 2016. Abstract
• V. Lomonaco and D. Maltoni, Comparing Incremental Learning Strategies for Convolutional Neural Networks , in proceedings 7th Workshop on Artificial Neural Networks in Pattern Recognition (ANNPR16), Ulm, Germany, September 2016. Abstract
• E.M. Rehn and D. Maltoni, Incremental Learning by Message Passing in Hierarchical Temporal Memory , Neural Computation, vol.26, no.8, pp.1763-1809, August 2014. Abstract
• D. Maltoni and E.M. Rehn, Incremental Learning by Message Passing in Hierarchical Temporal Memory , in proceedings 5th Workshop on Artificial Neural Networks in Pattern Recognition (ANNPR12), Trento (Italy), pp.24-35, September 2012. Abstract
• D. Maltoni, Pattern Recognition by Hierarchical Temporal Memory , Technical Report, DEIS - University of Bologna technical report, April 2011. Abstract