Deep variational Luenberger-type observer with dynamic objects channel-attention for stochastic video prediction-Reference-Cited by-同舟云学术

Deep variational Luenberger-type observer with dynamic objects channel-attention for stochastic video prediction

Published:2023-12-22 Issue:4 Volume:55 Page:728-740
ISSN:0020-7721
Container-title:International Journal of Systems Science
language:en
Short-container-title:International Journal of Systems Science

Author:

Wang Dong¹,Wen Chuanbo¹,Feng Xiaoliang¹

Affiliation:

1. School of Electrical Engineering, Shanghai Dianji University, Shanghai, People's Republic of China

Funder

National Natural Science Foundation of China

Capacity Building Project of Shanghai Local Colleges and Universities of China

Publisher

Informa UK Limited

Subject

Computer Science Applications,Theoretical Computer Science,Control and Systems Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/00207721.2023.2293686

Reference70 articles.

1. Abbaszadeh M. & Marquez H. J. (2008). LMI optimization approach to robust H∞ filtering for discrete-time nonlinear uncertain systems. IEEE 2008 American Control Conference .

2. Babaeizadeh M. Finn C. Erhan D. Campbell R. H. & Levine S. (2018). Stochastic variational video prediction. International Conference on Learning Representations .

3. Becker P. Pandya H. Gebhardt G. Zhao C. Taylor J. & Neumann G. (2019). Recurrent Kalman networks: Factorized inference in high-dimensional deep feature spaces. International Conference on Machine Learning .

4. Bhattacharyya A. Hanselmann M. Fritz M. Schiele B. & Straehle C. (2019). Conditional flow variational autoencoders for structured sequence prediction. Conference on Neural Information Processing Systems .

5. Boots B. Byravan A. & Fox D. (2014). Learning predictive models of a depth camera and manipulator from raw execution traces. International Conference on Robotics and Automation .

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Decentralized optimal control of large-scale partially unknown nonlinear mismatched interconnected systems based on dynamic event-triggered control;Neurocomputing;2024-02