Probabilistic Modeling and Uncertainty Awareness in Deep Learning
MCML Authors
Yuesong Shen
Dr.
* Former Member
Abstract
Yuesong Shen
Dr.
* Former Member
Abstract
This dissertation focuses on probabilistic modeling and uncertainty-aware approaches for deep learning. It is based on four papers that tackle the problem of uncertainty-aware deep learning, covering techniques such as post-hoc calibration, model aggregation, and Bayesian deep learning with variational inference. Also, an overview of related prior work is provided, which covers both classical and deep-learning-based approaches.
BibTeXKey: She25