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Peer-Review Record

Surface Approximation by Means of Gaussian Process Latent Variable Models and Line Element Geometry

Mathematics 2023, 11(2), 380; https://doi.org/10.3390/math11020380
by Ivan De Boi 1,*, Carl Henrik Ek 2 and Rudi Penne 1
Reviewer 1: Anonymous
Reviewer 2: Anonymous
Mathematics 2023, 11(2), 380; https://doi.org/10.3390/math11020380
Submission received: 14 December 2022 / Revised: 4 January 2023 / Accepted: 6 January 2023 / Published: 11 January 2023
(This article belongs to the Special Issue Statistical Data Modeling and Machine Learning with Applications II)

Round 1

Reviewer 1 Report

Please find attached the review report. 

Comments for author File: Comments.pdf

Author Response

Please see the attachment.

Author Response File: Author Response.docx

Reviewer 2 Report

This study introduces the GPLVM as an alternative to solve the surface detection and reconstruction tasks. The overall idea is straightforward. But what is lacking is the rigorous comparison between the proposed method and the existing methods. It seems that the authors just throw out this idea and preliminarily shows it works. It is hoped that the authors can show more examples to prove the advantage of their model from different perspectives (e.g., performance and accuracy).

Typo: line 189, "Forth" should be "Fourth".

Author Response

Please see the attachment.

Author Response File: Author Response.docx

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