google/uncertainty-baselines
A TensorFlow library of reference implementations for uncertainty and robustness benchmarking in deep learning.
Not currently ranked — collecting fresh signals.
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Uncertainty Baselines provides the research community with high-quality, forkable implementations of standard and state-of-the-art ML methods for uncertainty quantification. Built on TensorFlow, it offers baselines across tasks with minimal interdependencies so researchers can quickly prototype new approaches. The library also prescribes best practices for ML benchmarking and uncertainty evaluation.
Frequently asked
- What is google/uncertainty-baselines?
- A TensorFlow library of reference implementations for uncertainty and robustness benchmarking in deep learning.
- Is uncertainty-baselines open source?
- Yes — google/uncertainty-baselines is open source, released under the Apache-2.0 license.
- What language is uncertainty-baselines written in?
- google/uncertainty-baselines is primarily written in Python.
- How popular is uncertainty-baselines?
- google/uncertainty-baselines has 1.6k stars on GitHub.
- Where can I find uncertainty-baselines?
- google/uncertainty-baselines is on GitHub at https://github.com/google/uncertainty-baselines.