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license: mit
datasets:
  - mnist
metrics:
  - accuracy: 0.966
  - parameters: 1309
pipeline_tag: image-classification

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 and neural networks for a reference