3 papers
cs.LG2021
An Underexplored Dilemma between Confidence and Calibration in Quantized Neural Networks
Guoxuan Xia, Sangwon Ha, Tiago Azevedo +1
Modern convolutional neural networks (CNNs) are known to be overconfident in terms of their calibration on unseen input data. That is to say, they are more confident than they are…
cs.CV2020
Stochastic-YOLO: Efficient Probabilistic Object Detection under Dataset Shifts
Tiago Azevedo, René de Jong, Matthew Mattina +1
In image classification tasks, the evaluation of models' robustness to increased dataset shifts with a probabilistic framework is very well studied. However, object detection (OD)…
cs.LG2020
Towards a predictive spatio-temporal representation of brain data
Tiago Azevedo, Luca Passamonti, Pietro Liò +1
The characterisation of the brain as a "connectome", in which the connections are represented by correlational values across timeseries and as summary measures derived from graph t…