16 citations · 77 across the 29 of their papers we have counts for
5 papers · 1 filter
TrackFlow: Multi-Object Tracking with Normalizing Flows
Gianluca Mancusi, Aniello Panariello, Angelo Porrello +3
The field of multi-object tracking has recently seen a renewed interest in the good old schema of tracking-by-detection, as its simplicity and strong priors spare it from the compl…
On the Effectiveness of Equivariant Regularization for Robust Online Continual Learning
Lorenzo Bonicelli, Matteo Boschini, Emanuele Frascaroli +6
Humans can learn incrementally, whereas neural networks forget previously acquired information catastrophically. Continual Learning (CL) approaches seek to bridge this gap by facil…
Neuro-Symbolic Continual Learning: Knowledge, Reasoning Shortcuts and Concept Rehearsal
Emanuele Marconato, Gianpaolo Bontempo, Elisa Ficarra +3
We introduce Neuro-Symbolic Continual Learning, where a model has to solve a sequence of neuro-symbolic tasks, that is, it has to map sub-symbolic inputs to high-level concepts and…
Input Perturbation Reduces Exposure Bias in Diffusion Models
Mang Ning, Enver Sangineto, Angelo Porrello +2
Denoising Diffusion Probabilistic Models have shown an impressive generation quality, although their long sampling chain leads to high computational costs. In this paper, we observ…
Latent Spectral Regularization for Continual Learning
Emanuele Frascaroli, Riccardo Benaglia, Matteo Boschini +4
While biological intelligence grows organically as new knowledge is gathered throughout life, Artificial Neural Networks forget catastrophically whenever they face a changing train…