activity
20212023
most citedSlimmable Quantum Federated Learning

10 citations · 18 across the 14 of their papers we have counts for

collaborators

14 papers

cs.MA20232 cited

Quantum Multi-Agent Reinforcement Learning for Autonomous Mobility Cooperation

Soohyun Park, Jae Pyoung Kim, Chanyoung Park +2

For Industry 4.0 Revolution, cooperative autonomous mobility systems are widely used based on multi-agent reinforcement learning (MARL). However, the MARL-based algorithms suffer f…

cs.AI20231 cited

Two Tales of Platoon Intelligence for Autonomous Mobility Control: Enabling Deep Learning Recipes

Soohyun Park, Haemin Lee, Chanyoung Park +3

This paper presents the deep learning-based recent achievements to resolve the problem of autonomous mobility control and efficient resource management of autonomous vehicles and U…

cs.MA2023

Multi-Agent Reinforcement Learning for Cooperative Air Transportation Services in City-Wide Autonomous Urban Air Mobility

Chanyoung Park, Gyu Seon Kim, Soohyun Park +2

The development of urban-air-mobility (UAM) is rapidly progressing with spurs, and the demand for efficient transportation management systems is a rising need due to the multifacet…

cs.MA2023

Coordinated Multi-Agent Reinforcement Learning for Unmanned Aerial Vehicle Swarms in Autonomous Mobile Access Applications

Chanyoung Park, Haemin Lee, Won Joon Yun +2

This paper proposes a novel centralized training and distributed execution (CTDE)-based multi-agent deep reinforcement learning (MADRL) method for multiple unmanned aerial vehicles…

cs.DC2023

Workload-Aware Scheduling using Markov Decision Process for Infrastructure-Assisted Learning-Based Multi-UAV Surveillance Networks

Soohyun Park, Chanyoung Park, Soyi Jung +2

In modern networking research, infrastructure-assisted unmanned autonomous vehicles (UAVs) are actively considered for real-time learning-based surveillance and aerial data-deliver…

quant-ph20231 cited

EQuaTE: Efficient Quantum Train Engine for Dynamic Analysis via HCI-based Visual Feedback

Soohyun Park, Won Joon Yun, Chanyoung Park +4

This paper proposes an efficient quantum train engine (EQuaTE), a novel tool for quantum machine learning software which plots gradient variances to check whether our quantum neura…