Bayesian inference for deep learning

Rossi, Simone; Filippone, Maurizio
IJCAI 2021, 30th International Joint Conference on Artificial Intelligence, 19-26 August 2021, Montreal, Canada (Virtual Conference)

Throughout the last decade, the practical advancements and the theoretical understanding of deep learning (DL) models and practices has arguably reached a level of maturity such that it is the preferred choice for any practitioner seeking simple yet powerful solutions to solve machine learning (ML)-related problems. With this tutorial we aim to expose the participants to novel trends in DL for scenarios where quantification of uncertainty matters and we will discuss new and emerging trends in the Bayesian deep learning community.



Type:
Tutorial
City:
Montreal
Date:
2021-08-18
Department:
Data Science
Eurecom Ref:
6616
Copyright:
IJCAI

PERMALINK : https://www.eurecom.fr/publication/6616