Yanming Lai

Orcid: 0009-0008-5510-8760

According to our database¹, Yanming Lai authored at least 12 papers between 2021 and 2025.

Collaborative distances:

Dijkstra number² of five.
Erdős number³ of four.

Timeline

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PhD thesis

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On csauthors.net:

Bibliography

2025

Error Analysis of Three-Layer Neural Network Trained With PGD for Deep Ritz Method.

[BibT_eX]

[DOI]

Yuling Jiao

Yanming Lai

Yang Wang

IEEE Trans. Inf. Theory, July, 2025

Transformers Can Overcome the Curse of Dimensionality: A Theoretical Study from an Approximation Perspective.

[BibT_eX]

[DOI]

CoRR, April, 2025

Approximation Bounds for Transformer Networks with Application to Regression.

[BibT_eX]

[DOI]

CoRR, April, 2025

2024

Error Analysis of Three-Layer Neural Network Trained with PGD for Deep Ritz Method.

[BibT_eX]

[DOI]

Yuling Jiao

Yanming Lai

Yang Wang

CoRR, 2024

Convergence Analysis of Flow Matching in Latent Space with Transformers.

[BibT_eX]

[DOI]

CoRR, 2024

2023

Deep Neural Networks with ReLU-Sine-Exponential Activations Break Curse of Dimensionality in Approximation on Hölder Class.

[BibT_eX]

[DOI]

SIAM J. Math. Anal., August, 2023

Convergence Analysis of the Deep Galerkin Method for Weak Solutions.

[BibT_eX]

[DOI]

CoRR, 2023

2021

Analysis of Deep Ritz Methods for Laplace Equations with Dirichlet Boundary Conditions.

[BibT_eX]

[DOI]

CoRR, 2021

Convergence Analysis for the PINNs.

[BibT_eX]

[DOI]

CoRR, 2021

Error Analysis of Deep Ritz Methods for Elliptic Equations.

[BibT_eX]

[DOI]

CoRR, 2021

Convergence Rate Analysis for Deep Ritz Method.

[BibT_eX]

[DOI]

CoRR, 2021

Deep Neural Networks with ReLU-Sine-Exponential Activations Break Curse of Dimensionality on Hölder Class.

[BibT_eX]

[DOI]

CoRR, 2021

Yanming Lai

Timeline

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Bibliography

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