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Synthetic spectra challenging dataset — Jan Schuetzke | RDL Network

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Synthetic spectra challenging dataset

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Nathan J Szymanski

University of California, Berkeley

Synthetic spectra challenging dataset

Dataset en

Authors

JS
Jan Schuetzke
Nathan J Szymanski
University of California, Berkeley
MR
Markus Reischl

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Abstract

1 min read

Challenging dataset to evaluate ML/DL models for the classification of synthetic spectra

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Publication Info

DOI: 10.6084/m9.figshare.22188433
Year
Published: —
Language: en

Dataset Details

Link Of The Paper: https://doi.org/10.6084/m9.figshare.22188433

Timeline

Created:June 19, 2026

2022

A universal synthetic dataset for machine learning on spectroscopic data

Jan Schuetzke, Nathan J Szymanski, Markus Reischl

TRIO: Task-agnostic dataset representation optimized for automatic algorithm selection

Noy Cohen-Shapira, Lior Rokach

2021 IEEE International Conference on Data Mining (ICDM)

Transfer learning for time series classification using synthetic data generation

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