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Alexander-Hirschowitz theorem applied to neurovarieties in new arXiv paper

By PulseAugur Editorial · [1 sources] ·

Researchers Alex Massarenti and collaborators have published a paper on arXiv detailing the Alexander-Hirschowitz theorem as applied to neurovarieties. Their work focuses on the dimension and identifiability of neurovarieties associated with polynomial neural networks. The paper provides an independent geometric proof for dimension statements previously derived from finite identifiability, and also explores obstructions and global identifiability for multi-output architectures. AI

IMPACT Provides theoretical insights into the structure and identifiability of polynomial neural networks.

RANK_REASON Academic paper published on arXiv detailing mathematical theorems applied to neural networks. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Alexander-Hirschowitz theorem applied to neurovarieties in new arXiv paper

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Academic paper published on arXiv detailing mathematical theorems applied to neural networks. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · A. Massarenti, M. Mella ·

    The Alexander-Hirschowitz theorem for neurovarieties

    arXiv:2511.19703v2 Announce Type: replace-cross Abstract: We study the dimension and identifiability of neurovarieties associated to polynomial neural networks. We give an independent geometric proof that the linear bounds $d_i\geq 2n_i-1$ on the activation degrees imply non defe…

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