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Commits on Apr 8, 2021

• added arxiv link

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Commits on Apr 6, 2021

• updated link for the Siamese U-Net model

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Commits on Jul 29, 2020

• Update README.md

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• Update README.md

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Commits on Jun 17, 2020

• Update README.md

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• Update README.md

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• colab with a demo

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• Update README.md

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• Add files via upload

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• Create README.md

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Commits on Jul 4, 2019

• Moved codes around, added samples with multiprocessing on cpus, excluded some non-sense samples as a bonus.

  

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Commits on Jul 1, 2019

• Verbosity of runs - reducing the amount of printed clutter...

  

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• Plots for results

  

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• Cleanup dead branches of code, ideas

  

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• Series of tweaks and fixes, cleanup

  

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Commits on Jun 24, 2019

• Adding resume functionality to AL loop

  

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• Evaluation of unbalanced sets in several steps implemented

  

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• Tweaks with args

  

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Commits on Jun 7, 2019

• Trying a test MCBN implementation with the main AL loops (and prep for some additional acquisition functions)

  

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Commits on Jun 6, 2019

• Experiments with Entropy and BALD as an alternative to the Variance metric (however they seem to be slow)

  

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• Ensemble should average it's prediction

  

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• Robustness via VAL set loss and restarting training (in some fail cases)

  

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• Default to 1 model for Random (and other future) modes

  

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Commits on Jun 4, 2019

• Monte Carlo Batch Normalization alternative (and more efficient) approach via training on frozen model (except for 4 weights per each BN layer changing their local statistics)

  

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• Seeded AL and better plots

  

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• Cleanup

  

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• Added a cost plot

  

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• Server side path adjustments

  

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Commits on Jun 2, 2019

• First experiments with Monte Carlo Batch Normalization in Keras - one needs to predict in training mode (plus now I am predicting small subset of test samples (1 now) with a random batch from train…

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Commits on May 31, 2019

• setup instructions update

  

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• Added validation dataset (to both AL and baseline kfolds).

  

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• del old stuffs

  

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• move file

  

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Commits on May 30, 2019

• Loading entire dataset from pre-baked smaller h5 files.

  

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• Adding runners and bash files to run files more efficiently. Better evaluation with more plots.

  

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