Glassoformer: A Query-Sparse Transformer for Post-Fault Power Grid Voltage Prediction-Reference-Cited by-同舟云学术

Glassoformer: A Query-Sparse Transformer for Post-Fault Power Grid Voltage Prediction

Published:2022-05-23 Issue: Volume: Page:
ISSN:
Container-title:ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
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Author:

Zheng Yunling¹,Hu Carson¹,Lin Guang²,Yue Meng³,Wang Bao⁴,Xin Jack¹

Affiliation:

1. University of California,Department of Mathematics,Irvine

2. Purdue University,School of Mechanical Engineering,Department of Mathematics

3. Brookhaven National Laboratory,Interdisciplinary Science Department

4. The University of Utah,Department of Mathematics and Scientific Computing and Imaging Institute

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9745891/9746004/09747394.pdf?arnumber=9747394

Reference22 articles.

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3. Informer: Beyond efficient transformer for long sequence time-series forecasting;zhou;Proc of the Association for the Advancement of Artificial Intelligence,2021

4. Transformers are RNNs: Fast autoregressive transformers with linear attention;katharopoulos;Proceedings of the 37th International Conference on Machine Learning,2020

5. Rethinking attention with performers;choromanski;International Conference on Learning Representations,2021

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