Corpus ID: 195069328

BatchBALD: Efficient and Diverse Batch Acquisition for Deep Bayesian Active Learning

@inproceedings{Kirsch2019BatchBALDEA,
  title={BatchBALD: Efficient and Diverse Batch Acquisition for Deep Bayesian Active Learning},
  author={Andreas Kirsch and Joost R. van Amersfoort and Yarin Gal},
  booktitle={NeurIPS},
  year={2019}
}
  • Andreas Kirsch, Joost R. van Amersfoort, Yarin Gal
  • Published in NeurIPS 2019
  • Computer Science, Mathematics
  • We develop BatchBALD, a tractable approximation to the mutual information between a batch of points and model parameters, which we use as an acquisition function to select multiple informative points jointly for the task of deep Bayesian active learning. [...] Key Method We compare BatchBALD to the commonly used approach for batch data acquisition and find that the current approach acquires similar and redundant points, sometimes performing worse than randomly acquiring data. We finish by showing that, using…Expand Abstract
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