Detecting Out-of-Distribution Datapoints via Embeddings or Predictions

• cleanlab

  69 8,592 9.4 Python

  The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.

  

Many of you will likely find this useful -- our open-source team at https://cleanlab.ai has spent the last few years building out the much-needed standard python framework for all things #datacentricAI.

• dgl

  4 12,979 9.9 Python

  Python package built to ease deep learning on graph, on top of existing DL frameworks.

  

For trees/graphs, you’ll want a neural net that can take these as inputs for which I’m not sure a standard library exists. One recommendation is to checkout dgl: https://github.com/dmlc/dgl

• WorkOS

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  The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.

  

• detectron2

  49 28,671 7.5 Python

  Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.

  

You should already be able to use the code for object detection data if you do the outlier detection based on feature embeddings rather than predictions! You just need to get embeddings out of your object detection network, as demonstrated here for example: https://detectron2.readthedocs.io/en/latest/tutorials/models.html#partially-execute-a-model https://github.com/facebookresearch/detectron2/issues/5

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