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DeepLM: Large-scale Nonlinear Least Squares on Deep Learning Frameworks using Stochastic Domain Decomposition (CVPR 2021)

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DeepLM

Jingwei Huang, Shan Huang, and Mingwei Sun. DeepLM: Large-scale Nonlinear Least Squares on Deep Learning Frameworks using Stochastic Domain Decomposition, CVPR 2021

DeepLM Results

Run

Please install the following

  1. pytorch.
  2. OpenMP (optional)

Then, run the example via

sh example.sh

Data Description

A full set of test data can be downloaded from the BAL page (Software & Data -> Available Dataset).

Other Application

Please check the examples folder for more application and features.

Author

© 2021 Jingwei Huang All Rights Reserved

IMPORTANT: If you use this code please cite the following in any resulting publication:

@inproceedings{huang2021deeplm,
  title={DeepLM: Large-scale Nonlinear Least Squares on Deep Learning Frameworks using Stochastic Domain Decomposition},
  author={Huang, Jingwei and Huang, Shan and Sun, Mingwei},
  booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
  pages={10308--10317},
  year={2021}
}

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DeepLM: Large-scale Nonlinear Least Squares on Deep Learning Frameworks using Stochastic Domain Decomposition (CVPR 2021)

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