3 papers
cs.LG2021
Avalanche: an End-to-End Library for Continual Learning
Vincenzo Lomonaco, Lorenzo Pellegrini, Andrea Cossu +25
Learning continually from non-stationary data streams is a long-standing goal and a challenging problem in machine learning. Recently, we have witnessed a renewed and fast-growing…
physics.data-an2019
DeepRICH: Learning Deeply Cherenkov Detectors
Cristiano Fanelli, Jary Pomponi
Imaging Cherenkov detectors are largely used for particle identification (PID) in nuclear and particle physics experiments, where developing fast reconstruction algorithms is becom…
cs.LG2019
Efficient Continual Learning in Neural Networks with Embedding Regularization
Jary Pomponi, Simone Scardapane, Vincenzo Lomonaco +1
Continual learning of deep neural networks is a key requirement for scaling them up to more complex applicative scenarios and for achieving real lifelong learning of these architec…