5 citations · 7 across the 4 of their papers we have counts for
7 papers
Continual Pre-Training Mitigates Forgetting in Language and Vision
Andrea Cossu, Tinne Tuytelaars, Antonio Carta +3
Pre-trained models are nowadays a fundamental component of machine learning research. In continual learning, they are commonly used to initialize the model before training on the s…
Avalanche RL: a Continual Reinforcement Learning Library
Nicolò Lucchesi, Antonio Carta, Vincenzo Lomonaco +1
Continual Reinforcement Learning (CRL) is a challenging setting where an agent learns to interact with an environment that is constantly changing over time (the stream of experienc…
AI-as-a-Service Toolkit for Human-Centered Intelligence in Autonomous Driving
Valerio De Caro, Saira Bano, Achilles Machumilane +11
This paper presents a proof-of-concept implementation of the AI-as-a-Service toolkit developed within the H2020 TEACHING project and designed to implement an autonomous driving per…
TEACHING -- Trustworthy autonomous cyber-physical applications through human-centred intelligence
Davide Bacciu, Siranush Akarmazyan, Eric Armengaud +32
This paper discusses the perspective of the H2020 TEACHING project on the next generation of autonomous applications running in a distributed and highly heterogeneous environment c…
Continual Learning with Echo State Networks
Andrea Cossu, Davide Bacciu, Antonio Carta +2
Continual Learning (CL) refers to a learning setup where data is non stationary and the model has to learn without forgetting existing knowledge. The study of CL for sequential pat…
Distilled Replay: Overcoming Forgetting through Synthetic Samples
Andrea Rosasco, Antonio Carta, Andrea Cossu +2
Replay strategies are Continual Learning techniques which mitigate catastrophic forgetting by keeping a buffer of patterns from previous experiences, which are interleaved with new…