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New theory quantifies Gaussian-process limits in neural networks · 2 sources tracked

By PulseAugur Editorial · [2 sources] ·

Researchers have developed a quantitative theory for the Gaussian-process limit of random neural networks using tensor programs. Their work provides explicit finite-width error bounds, detailing the convergence rate in Wasserstein distance between finite-network executions and their theoretical Gaussian-process limits. This framework is designed to be architecture-agnostic, applicable to various neural network designs including feed-forward, recurrent, and transformer-type architectures. AI

IMPACT Provides a theoretical framework for understanding neural network behavior at scale, potentially aiding in the design of more robust and predictable models.

RANK_REASON The cluster contains an academic paper detailing theoretical advancements in neural network analysis.

Read on arXiv stat.ML →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

New theory quantifies Gaussian-process limits in neural networks · 2 sources tracked

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The cluster contains an academic paper detailing theoretical advancements in neural network analysis.
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paper, model release
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COVERAGE [2]

  1. arXiv stat.ML TIER_1 English(EN) · Andrea Agazzi, Eloy Mosig Garc\'ia, Dario Trevisan ·

    Quantitative Gaussian-Process limits of Tensor Programs

    arXiv:2607.06290v1 Announce Type: cross Abstract: We study the infinite-width Gaussian-process limit of random neural networks through the lens of tensor programs, and we provide a quantitative convergence theory in Wasserstein distance. Our main result gives explicit finite-widt…

  2. arXiv stat.ML TIER_1 English(EN) · Dario Trevisan ·

    Quantitative Gaussian-Process limits of Tensor Programs

    We study the infinite-width Gaussian-process limit of random neural networks through the lens of tensor programs, and we provide a quantitative convergence theory in Wasserstein distance. Our main result gives explicit finite-width error bounds, of order inverse square-root of th…

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