Lennon J. Shikhman

Scientific Machine Learning · Applied Mathematics

Citing papers

One Operator to Rule Them All? On Boundary-Indexed Operator Families in Neural PDE Solvers

6 papers cite this work.

  1. Cellular Sheaf Neural Operators for Structure-Preserving Surrogate Modeling of Constrained PDEs

    Lennon J. Shikhman · Shane Gilbertie

    arXiv · 2026

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  2. Diagnosing Failure Modes of Neural Operators Across Diverse PDE Families

    Lennon Shikhman

    Transactions on Machine Learning Research · 2026

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  3. Does Text Steer Neural PDE Surrogates? A Controlled Diagnostic with OperatorCLIP

    Aadi Dash · Lennon J. Shikhman · Michael Galarnyk

    NeurIPS 2026 Workshop on Representations for the Physical Sciences · 2026

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  4. Inverse Learning of Latent Risk-Neutral Densities from Irregular Option Quotes

    Lennon J. Shikhman · Michael Galarnyk · Aadi Dash · Nicholas A. Welsh

    7th ACM International Conference on AI in Finance (ICAIF 2026) · 2026

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  5. Operator Boosting Produces Pareto-Efficient PDE Surrogates

    Lennon J. Shikhman

    arXiv · 2026

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  6. Semigroup Consistency as a Diagnostic for Learned Physics Simulators

    Lennon J. Shikhman

    ICML 2026 Workshop on AI for Physics · 2026

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