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

6 July 2022

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

6 / 6 papers shown

Title
Transformers for scientific data: a pedagogical review for astronomers Dimitrios Tanoglidis Bhuvnesh Jain Helen Qu MedIm ViT 19 1 0 18 Oct 2023
Self-Supervised Learning for Modeling Gamma-ray Variability in Blazars A. Brill MedIm 16 1 0 15 Feb 2023
Astronomia ex machina: a history, primer, and outlook on neural networks in astronomy Michael J. Smith James E. Geach 35 32 0 07 Nov 2022
Transformers in Vision: A Survey Salman Khan Muzammal Naseer Munawar Hayat Syed Waqas Zamir F. Khan M. Shah ViT 227 2,430 0 04 Jan 2021
Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting Haoyi Zhou Shanghang Zhang J. Peng Shuai Zhang Jianxin Li Hui Xiong Wan Zhang AI4TS 169 3,885 0 14 Dec 2020
A Decomposable Attention Model for Natural Language Inference Ankur P. Parikh Oscar Täckström Dipanjan Das Jakob Uszkoreit 201 1,367 0 06 Jun 2016