receptive_field_analysis_toolbox

A toolbox for receptive field analysis and visualizing neural network architectures (by MLRichter)
Add to my DEV experience Pytorch Visualization Deep Learning neural-networks Machine Learning neural-architecture-optimization neural-architecture-search Tensorflow receptive-field receptive-field-analysis HacktoberFest
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receptive_field_analysis_toolbox reviews and mentions

Posts with mentions or reviews of receptive_field_analysis_toolbox. We have used some of these posts to build our list of alternatives and similar projects.
  • [D] Is neural network architecture just "alchemy"?
    1 project | /r/MachineLearning | 9 Feb 2022
    On a more personal note, the interaction of input resolution and receptive field allows you to pretty accurately determine if your network is too deep. I created an OpenSource-library for people to check this out: https://github.com/MLRichter/receptive_field_analysis_toolbox. Also, I found out in this publication that the intrinsic dimensionality of the data inside a layer can be analyzed in life during training pretty efficiently and used as a guideline to adjust the width of the network. So, there are some ways to guide neural architecture design and there maybe are more to come, but that's just me being optimistic about my own research.
  • GitHub - MLRichter/receptive_field_analysis_toolbox
    1 project | /r/techtravel | 10 Jan 2022

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Basic receptive_field_analysis_toolbox repo stats
2
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0.0
25 days ago

MLRichter/receptive_field_analysis_toolbox is an open source project licensed under MIT License which is an OSI approved license.

The primary programming language of receptive_field_analysis_toolbox is Python.

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