Equivariant machine learning from classical physics – Soledad Villar

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Soledad Villar - Introduction to equivariant machine learning - IPAM at UCLA

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Soledad Villar, John Hopkins University: Exact and approximate symmetries in machine learning models

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Soledad Villar: Units-equivariant machine learning

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Soledad Villar, Equivariant machine learning and dimensional analysis, 2022.03.22

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Units-equivariant machine learning, Soledad Villar@JHU

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Soledad Villar - Dimensionality reduction and matching datasets

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Soledad Villar: Units-equivariant machine learning

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Soledad Villar, Galois theory and low-rank matrix completion meet machine learning, 2024.10.15

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Dr. Soledad Villar -- Exploiting symmetries in machine learning models

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Soledad Villar: \

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DDPS | The passive symmetries of machine learning by Soledad Villar

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Enforcing exact group equivariances in machine learning - Soledad Villar - FFT May 23rd, 2022

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1W-MINDS: Sep 15, 2022, Soledad Villar, Equivariant machine learning from invariant functions

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Equivariant Machine Learning Structured Like Classical Physics

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Certified Sub-Linear Lower Bounds for K-Means Clustering

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Scalars are Universal: Gauge-equivariant Machine Learning, Structured Like Classical Physics

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Interpretable Feature Selection

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Approximately equivariant graph networks

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