71 citations · 105 across the 7 of their papers we have counts for
8 papers
Latent Discriminant deterministic Uncertainty
Gianni Franchi, Xuanlong Yu, Andrei Bursuc +3
Predictive uncertainty estimation is essential for deploying Deep Neural Networks in real-world autonomous systems. However, most successful approaches are computationally intensiv…
MUAD: Multiple Uncertainties for Autonomous Driving, a benchmark for multiple uncertainty types and tasks
Gianni Franchi, Xuanlong Yu, Andrei Bursuc +5
Predictive uncertainty estimation is essential for safe deployment of Deep Neural Networks in real-world autonomous systems. However, disentangling the different types and sources…
Encoding the latent posterior of Bayesian Neural Networks for uncertainty quantification
Gianni Franchi, Andrei Bursuc, Emanuel Aldea +2
Bayesian neural networks (BNNs) have been long considered an ideal, yet unscalable solution for improving the robustness and the predictive uncertainty of deep neural networks. Whi…
One Versus all for deep Neural Network Incertitude (OVNNI) quantification
Gianni Franchi, Andrei Bursuc, Emanuel Aldea +2
Deep neural networks (DNNs) are powerful learning models yet their results are not always reliable. This is due to the fact that modern DNNs are usually uncalibrated and we cannot…
TRADI: Tracking deep neural network weight distributions for uncertainty estimation
Gianni Franchi, Andrei Bursuc, Emanuel Aldea +2
During training, the weights of a Deep Neural Network (DNN) are optimized from a random initialization towards a nearly optimum value minimizing a loss function. Only this final st…
Confidence-Weighted Local Expression Predictions for Occlusion Handling in Expression Recognition and Action Unit detection
Arnaud Dapogny, Kévin Bailly, Séverine Dubuisson
Fully-Automatic Facial Expression Recognition (FER) from still images is a challenging task as it involves handling large interpersonal morphological differences, and as partial oc…