Soon-Seo Park

According to our database1, Soon-Seo Park authored at least 14 papers between 2016 and 2021.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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In proceedings 
Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2021
Bayesian Nonparametric State-Space Model for System Identification with Distinguishable Multimodal Dynamics.
J. Aerosp. Inf. Syst., March, 2021

Distilling a Hierarchical Policy for Planning and Control via Representation and Reinforcement Learning.
Proceedings of the IEEE International Conference on Robotics and Automation, 2021

2019
Optimal Target Assignment with Seamless Handovers for Networked Radars.
Sensors, 2019

Topology-guided path integral approach for stochastic optimal control in cluttered environment.
Robotics Auton. Syst., 2019

Informative Planning of Mobile Sensor Networks in GPS-Denied Environments.
CoRR, 2019

Online Gaussian Process State-Space Models: Learning and Planning for Partially Observable Dynamical Systems.
CoRR, 2019

A Distributed ADMM Approach to Non-Myopic Path Planning for Multi-Target Tracking.
IEEE Access, 2019

Ballistic Object Trajectory and Launch Point Estimation from Radar Measurements using Long-Short Term Memory Networks.
Proceedings of the 7th International Conference on Robot Intelligence Technology and Applications, 2019

2018
A Distributed ADMM Approach to Informative Trajectory Planning for Multi-Target Tracking.
CoRR, 2018

Adaptive Path-Integral Approach to Representation Learning and Planning for Dynamical Systems.
CoRR, 2018

Potential Game-Based Non-Myopic Sensor Network Planning for Multi-Target Tracking.
IEEE Access, 2018

Adaptive Path-Integral Autoencoders: Representation Learning and Planning for Dynamical Systems.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Adaptive Path-Integral Approach for Representation Learning and Planning.
Proceedings of the 6th International Conference on Learning Representations, 2018

2016
Asymptotically Optimal Sampling-Based Algorithms for Topological Motion Planning.
CoRR, 2016


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