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license: mit |
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datasets: |
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- mnist |
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metrics: |
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- accuracy |
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pipeline_tag: image-classification |
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A super tiny mnist model to demostrate the potential of the learnable activation - OptAEG-V1. |
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The model can reach 96.6% accuracy with only 1.3k parameters. |
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The OptAEG-V1 learnable activation is based on a theory of Arithmetic Expression Geometry which is still in developing. |
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Please visit the draft papers on [theory](https://github.com/mountain/aeg-paper) and [neural networks](https://github.com/mountain/optim-aeg) for a reference |
