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Paper on covering-space normalizing flows withdrawn by author

By PulseAugur Editorial · [1 sources] ·

This paper, "Covering-Space Normalizing Flows: Approximating Pushforwards on Lens Spaces," introduces a method for constructing pushforward distributions using a universal covering map. The approach aims to approximate these distributions with flows on lens spaces, offering benefits such as deleting redundancies for symmetric distributions. The authors demonstrate its application by approximating pushforwards of von Mises-Fisher-induced target densities and a Z_12-symmetric Boltzmann distribution modeling benzene. AI

IMPACT Introduces a new mathematical framework for approximating complex distributions, potentially aiding in generative modeling and data analysis.

RANK_REASON This is a research paper published on arXiv detailing a novel methodology in machine learning. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.LG →

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

Paper on covering-space normalizing flows withdrawn by author

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This is a research paper published on arXiv detailing a novel methodology in machine learning. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.LG TIER_1 English(EN) · William Ghanem ·

    Covering-Space Normalizing Flows: Approximating Pushforwards on Lens Spaces

    arXiv:2511.22882v2 Announce Type: replace Abstract: We construct pushforward distributions via the universal covering map rho: S^3 -> L(p;q) with the goal of approximating these distributions using flows on L(p;q). We highlight that our method deletes redundancies in the case of …

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