Boschini, Matteo
- Dark Experience for General Continual Learning: a Strong, Simple Baseline
2020/04/15 by Pietro Buzzega, Buzzega, Pietro, M. Boschini +8 · 69 citations
Computer Science · Medicine · #Anomaly Detection Techniques and Applications #COVID-19 diagnosis using AI #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- Rethinking Experience Replay: a Bag of Tricks for Continual Learning
2020/10/12 by Pietro Buzzega, Matteo Boschini, Buzzega, Pietro +5 · 6 citations
Computer Science · #Domain Adaptation and Few-Shot Learning #Machine Learning and ELM #Multimodal Machine Learning Applications
- On the Effectiveness of Lipschitz-Driven Rehearsal in Continual Learning
2022/10/12 by Lorenzo Bonicelli, Bonicelli, Lorenzo, M. Boschini +7 · 6 citations
Computer Science · #Artificial Intelligence (cs.AI) #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Human Pose and Action Recognition #Machine Learning (cs.LG) #Multimodal Machine Learning Applications
- Semantic Residual Prompts for Continual Learning
2024/03/11 by Martin Menabue, Emanuele Frascaroli, Menabue, Martin +11 · 7 citations
Computer Science · #Domain Adaptation and Few-Shot Learning
- Transfer without Forgetting
2022/06/01 by M. Boschini, Boschini, Matteo, Lorenzo Bonicelli +13 · 2 citations
Computer Science · Engineering · #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Geophysical Methods and Applications #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Multimodal Machine Learning Applications
- Non-adiabatic dynamics of eccentric black-hole binaries in post-Newtonian theory
2025/02/10 by Giulia Fumagalli, Nicholas Loutrel, Fumagalli, Giulia +5 · 3 citations
Physics and Astronomy · #Black Holes and Theoretical Physics #Cosmology and Gravitation Theories #FOS: Physical sciences #General Relativity and Quantum Cosmology (gr-qc) #High Energy Astrophysical Phenomena (astro-ph.HE) #Relativity and Gravitational Theory