Stop the war!

Остановите войну!

for scientists:

default search action

combined dblp search
author search
venue search
publication search

ask others

"On the Difficulty of Epistemic Uncertainty Quantification in Machine ..."

Viktor Bengs, Eyke Hüllermeier, Willem Waegeman (2022)

> Home

Details and statistics

DOI: 10.48550/ARXIV.2203.06102

access: open

type: Informal or Other Publication

metadata version: 2022-03-16

- view
  - electronic edition via DOI (open access)
  authority control:
- export record
  dblp key:
  - journals/corr/abs-2203-06102
- ask others
- share record
  persistent URL:
  - https://dblp.org/rec/journals/corr/abs-2203-06102
Viktor Bengs, Eyke Hüllermeier, Willem Waegeman:
On the Difficulty of Epistemic Uncertainty Quantification in Machine Learning: The Case of Direct Uncertainty Estimation through Loss Minimisation. CoRR abs/2203.06102 (2022)

a service of

manage site settings

To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.