Approximating Latent Manifolds in Neural Networks via Vanishing Ideals

Nico Pelleriti; Max Zimmer; Elias Samuel Wirth; Sebastian Pokutta

2025 ICML ICML 2025

Approximating Latent Manifolds in Neural Networks via Vanishing Ideals

Abstract

No abstract available. No abstract was captured for this paper when its proceedings were scraped - most often an older edition published without one online. How the corpus is built.

Authors

Nico Pelleriti, Max Zimmer, Elias Samuel Wirth, Sebastian Pokutta

Topics

Artificial Intelligence > Core AI > Interpretability Machine Learning > Core Methods > Representation Learning Deep Learning > Architectures > Neural Networks

Keywords

neural architecture vanishing ideal polynomial generator latent manifold truncations linearly separable features

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