Deep Learning Reading Group
This is eighth session of 2024. We'll be discussing:
(Methods) Single-Model Uncertainties for Deep Learning (https://arxiv.org/abs/1811.00908):
- Quantifying uncertainties for the predictions of deep learning models is a difficult task in general, but remains important for drawing inferences. Here, a simple universal scheme is proposed to augment deep learning models with an additional input that one can adjust to predict arbitrary quantiles.
Upcoming material is to be read before each session, so that it may be discussed in an open format. Staff and students from all backgrounds who are interested in these topics are welcome. If you are interested but haven't been to a session yet, come along. There is no need to have participated in all sessions.