pith. sign in

Data complexity estimates for operator learning.arXiv preprint arXiv:2405.15992, 2024

4 Pith papers cite this work. Polarity classification is still indexing.

4 Pith papers citing it

years

2026 4

verdicts

UNVERDICTED 4

representative citing papers

Transpose-free linear algebra

math.NA · 2026-05-31 · unverdicted · novelty 7.0

Establishes non-identifiability results and query lower bounds showing transpose-free matvec access provides limited information for core linear algebra tasks.

citing papers explorer

Showing 4 of 4 citing papers.

  • Transpose-free linear algebra math.NA · 2026-05-31 · unverdicted · none · ref 48

    Establishes non-identifiability results and query lower bounds showing transpose-free matvec access provides limited information for core linear algebra tasks.

  • Is Zero-Shot Super-Resolution Possible in Operator Learning? stat.ML · 2026-05-29 · unverdicted · none · ref 52

    Zero-shot super-resolution is information-theoretically impossible for some simple operators but possible under Hölder smoothness of outputs, accompanied by generalization bounds.

  • From Spectral Methods to Sample Complexity Bounds for Fourier Neural Operators stat.ML · 2026-07-01 · unverdicted · none · ref 34

    FNOs achieve polynomial sample complexity for learning time-T solution operators of dissipative evolution equations when those operators admit stable spectral discretizations, with rates depending on smoothness, dimension, and nonlinearity type.

  • Efficient Approximation for Encoder--Decoder Neural Operators via Variation Spaces stat.ML · 2026-05-31 · unverdicted · none · ref 19

    Introduces variation spaces for nonlinear operators and derives dimension-independent approximation bounds of order N^{-1/2} plus encoding errors for encoder-decoder two-layer networks, yielding algebraic rates under polynomial encoding decay.