Replaces standard activation functions like ReLU or Swish in deep learning models. Implements a smooth, non-monotonic mathematical curve to improve gradient flow and model accuracy during training.
Tech Stack
Jupyter NotebookAI, ML & Data
Why Mish?
• Improved gradient propagation
• Self-regularizing properties
• Easy integration with PyTorch/TensorFlow
Limitations
• Higher compute cost than ReLU
• Experimental status
• Limited hardware acceleration support
2/24/2026
Last Update
128
Forks
0
Issues
MIT
License
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