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Paper analyzes floating-point neural network expressivity

By PulseAugur Editorial · [2 sources] ·

Researchers have published a paper exploring the expressive power of neural networks operating with floating-point arithmetic, moving beyond theoretical models that assume exact real numbers. The study introduces a framework to analyze how arbitrary reduction orders and inexact activation implementations affect a network's ability to represent functions. This work establishes conditions under which floating-point neural networks can achieve universal representability, extending previous findings to a wider range of practical activation functions. AI

IMPACT This research provides a more realistic theoretical understanding of neural network behavior in practical, finite-precision environments.

RANK_REASON The cluster contains a research paper published on arXiv detailing theoretical advancements in neural network expressivity.

Read on arXiv cs.LG →

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

Paper analyzes floating-point neural network expressivity

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The cluster contains a research paper published on arXiv detailing theoretical advancements in neural network expressivity.
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COVERAGE [2]

  1. arXiv cs.LG TIER_1 English(EN) · Yeachan Park, Geonho Hwang, Wonyeol Lee, Sejun Park ·

    Expressive Power of Floating-Point Neural Networks with Arbitrary Reduction Orders and Inexact Activation Implementations

    arXiv:2605.28704v1 Announce Type: new Abstract: Most existing expressivity theories for neural networks assume exact real arithmetic, whereas practical neural networks are executed under finite-precision floating-point arithmetic with implementation-dependent execution semantics.…

  2. arXiv cs.LG TIER_1 English(EN) · Sejun Park ·

    Expressive Power of Floating-Point Neural Networks with Arbitrary Reduction Orders and Inexact Activation Implementations

    Most existing expressivity theories for neural networks assume exact real arithmetic, whereas practical neural networks are executed under finite-precision floating-point arithmetic with implementation-dependent execution semantics. Recent works have begun studying the expressive…

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