straycat on Nostr: grapevine math and neural network math are more similar than I had thought ...
grapevine math and neural network math are more similar than I had thought
Similarity: Both make use of a weighted sum.
Difference: Grapevine equation divides by the sum of weights (since it’s a weighted average), something you don’t do with neural networks.
Similarity: Neural networks multiply by the sigma function; the grapevine multiplies by a function that maps weights onto confidence. Both functions are nonlinear.
Difference: neural networks have a ‘bias’ parameter which does not show up in the grapevine equation.
Published at
2024-09-25 02:25:02Event JSON
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"content": "grapevine math and neural network math are more similar than I had thought \n\nSimilarity: Both make use of a weighted sum.\n\nDifference: Grapevine equation divides by the sum of weights (since it’s a weighted average), something you don’t do with neural networks.\n\nSimilarity: Neural networks multiply by the sigma function; the grapevine multiplies by a function that maps weights onto confidence. Both functions are nonlinear.\n\nDifference: neural networks have a ‘bias’ parameter which does not show up in the grapevine equation.",
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