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Scaling
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Classroom Contents
Gaussian Pre-Activations in Neural Networks: Myth or Reality?
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- 1 Introduction
- 2 Scaling
- 3 Framework
- 4 Naive heuristic
- 5 Outline
- 6 Edge of Cows
- 7 Recurrence Equation
- 8 Gaussian PreActivations
- 9 The Edge of Chaos
- 10 Experiments
- 11 Gaussian regulations
- 12 Assumption of edge of chaos
- 13 Preservation of variance
- 14 Solution
- 15 Summary
- 16 Constraints
- 17 Density
- 18 activation functions
- 19 numerical approximations
- 20 training experiments
- 21 training losses
- 22 conclusion
- 23 future work
- 24 questions
- 25 data patterns
- 26 impossibility results
- 27 Cons
- 28 Training Loss
