Approximating Latent Manifolds in Neural Networks via Vanishing Ideals
Published in International Conference on Machine Learning (ICML), 2025
This paper introduces a novel approach to understanding and approximating latent manifolds in neural networks using tools from algebraic geometry, specifically vanishing ideals.
Recommended citation: Pelleriti, N., Zimmer, M., Wirth, E., & Pokutta, S. (2025). Approximating Latent Manifolds in Neural Networks via Vanishing Ideals. International Conference on Machine Learning (ICML).
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