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Don't Pay Attention to the Noise: Learning Self-supervised
  Representations of Light Curves with a Denoising Time Series Transformer

Don't Pay Attention to the Noise: Learning Self-supervised Representations of Light Curves with a Denoising Time Series Transformer

6 July 2022
M. Morvan
N. Nikolaou
K. H. Yip
Ingo P. Waldmann
    AI4TS
ArXiv (abs)PDFHTML

Papers citing "Don't Pay Attention to the Noise: Learning Self-supervised Representations of Light Curves with a Denoising Time Series Transformer"

4 / 4 papers shown
Title
Masked Autoencoders for Ultrasound Signals: Robust Representation Learning for Downstream Applications
Masked Autoencoders for Ultrasound Signals: Robust Representation Learning for Downstream Applications
Immanuel Roßteutscher
Klaus S. Drese
Thorsten Uphues
100
0
0
28 Aug 2025
Transformers for scientific data: a pedagogical review for astronomers
Transformers for scientific data: a pedagogical review for astronomers
Dimitrios Tanoglidis
Bhuvnesh Jain
Helen Qu
MedImViT
131
2
0
18 Oct 2023
Self-Supervised Learning for Modeling Gamma-ray Variability in Blazars
Self-Supervised Learning for Modeling Gamma-ray Variability in Blazars
A. Brill
MedIm
72
1
0
15 Feb 2023
Astronomia ex machina: a history, primer, and outlook on neural networks
  in astronomy
Astronomia ex machina: a history, primer, and outlook on neural networks in astronomyRoyal Society Open Science (RSOS), 2022
Michael J. Smith
James E. Geach
179
48
0
07 Nov 2022
1