google / uncertainty-baselines
High-quality implementations of standard and SOTA methods on a variety of tasks.
Why this job: topics: neural-networks, tensorflow, deep-learning, machine-learning
What it does
The goal of Uncertainty Baselines is to provide a template for researchers to build on. The baselines can be a starting point for any new ideas, applications, and/or for communicating with other uncertainty and robustness researchers. This is done in three ways:
Get started
pip install "git+https://github.com/google/uncertainty-baselines.git#egg=uncertainty_baselines" - Maintenance
- Active
- Last commit today
- Stars
- 1,602
- +1 this week
- Licence
- Apache-2.0
- Allows business use
- Downloads for
- None listed
- No release files
- Latest version
- None yet
- No releases
- Built with
- Python
- 95% of the code
Is it looked after?
- Contributors
- 3
- Last 90 days
- Issues
- 44% closed
- 50 still open
- Pull requests
- 865 merged
- 75 waiting
- Releases
- None
- Never published
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More: languages, topics and project record
Languages
- Python 95%
- Jupyter Notebook 5%
Topics
- bayesian-methods
- deep-learning
- machine-learning
- data-science
- tensorflow
- neural-networks
- statistics
- probabilistic-programming
Project record
- JobAI libraries and models
- StatusListed
- Commits1,198
- Forks226
- Watching21
- Stars in 28 days+5
- CreatedJul 16, 2020
- First seen by usNov 7, 2026
- CheckedNov 12, 2026