Why and When Deep is Better than Shallow: Implementation-Agnostic State-Transition Model of Deep Learning

arXiv:2505.15064 · cs.LG, math.DS, stat.ML · Submitted 2025-05-21 · Read on arXiv

cs.LG, math.DS, stat.ML

Submitted: 2025-05-21

Updated: 2026-09-26

Terminology

• Generalization — 24× in this paper · explained in 13 episodes
• Generalization Bounds — 7× in this paper · explained in 2 episodes
• Core — 5× in this paper · explained in 2 episodes
• Benchmark — 4× in this paper · explained in 2 episodes
• Adaptivity — 2× in this paper · explained in 1 episode
• Sample Complexity — 2× in this paper · explained in 15 episodes
• Abstraction — 1× in this paper · explained in 1 episode
• Activation Function — 1× in this paper · explained in 1 episode
• Curse of Dimensionality — 1× in this paper · explained in 6 episodes
• Diffusion Model — 1× in this paper · explained in 8 episodes
• Diffusion Models — 1× in this paper · explained in 6 episodes
• Hilbert Space — 1× in this paper · explained in 2 episodes
• Iterative Refinement — 1× in this paper · explained in 3 episodes
• Over-smoothing — 1× in this paper · explained in 4 episodes
• Quantization — 1× in this paper · explained in 12 episodes

Sources

• Neural Operator: Learning Maps Between Function Spaces

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