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Deep Ensembles: A Loss Landscape Perspective

Deep Ensembles: A Loss Landscape Perspective

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Deep Ensembles: A Loss Landscape Perspective

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  1. 1 Intro
  2. 2 Overview
  3. 3 Hypothesis
  4. 4 Background Research
  5. 5 Measuring function similarity within and
  6. 6 Subspace sampling within and across trajectories
  7. 7 Loss and function similarity in prediction space
  8. 8 Evaluating the effects of ensembling and
  9. 9 Conclusion
  10. 10 Questions, comments, ideas

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