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optaeg-v1-mnist-supertiny-1p3k

Image Classification

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mingli commited on Jan 26

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 A super tiny mnist model to demostrate the potential of the learnable activation - OptAEG-V1.
-The model can reach 96.6% accuracy with only a 1.3k parameter-size.
 The OptAEG-V1 learnable activation is based on a theory of Arithmetic Expression Geometry which is still in developing.
 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

 A super tiny mnist model to demostrate the potential of the learnable activation - OptAEG-V1.
+The model can reach 96.6% accuracy with only 1.3k parameters.
 The OptAEG-V1 learnable activation is based on a theory of Arithmetic Expression Geometry which is still in developing.
 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