most citedIntroduction to Quantum Reinforcement Learning: Theory and PennyLane-based Implementation

8 citations · 18 across the 5 of their papers we have counts for

collaborators

5 papers

quant-ph20222 cited

Quantum Multi-Agent Reinforcement Learning via Variational Quantum Circuit Design

Won Joon Yun, Yunseok Kwak, Jae Pyoung Kim +4

In recent years, quantum computing (QC) has been getting a lot of attention from industry and academia. Especially, among various QC research topics, variational quantum circuit (V…

quant-ph20222 cited

Quantum Distributed Deep Learning Architectures: Models, Discussions, and Applications

Yunseok Kwak, Won Joon Yun, Jae Pyoung Kim +4

Although deep learning (DL) has already become a state-of-the-art technology for various data processing tasks, data security and computational overload problems often arise due to…

cs.LG20218 cited

Introduction to Quantum Reinforcement Learning: Theory and PennyLane-based Implementation

Yunseok Kwak, Won Joon Yun, Soyi Jung +2

The emergence of quantum computing enables for researchers to apply quantum circuit on many existing studies. Utilizing quantum circuit and quantum differential programming, many r…

quant-ph20214 cited

Quantum Neural Networks: Concepts, Applications, and Challenges

Yunseok Kwak, Won Joon Yun, Soyi Jung +1

Quantum deep learning is a research field for the use of quantum computing techniques for training deep neural networks. The research topics and directions of deep learning and qua…

eess.SY20212 cited

Quantum Scheduling for Millimeter-Wave Observation Satellite Constellation

Joongheon Kim, Yunseok Kwak, Soyi Jung +1

In beyond 5G and 6G network scenarios, the use of satellites has been actively discussed for extending target monitoring areas, even for extreme circumstances, where the monitoring…