Videos

Research Talks

An Introduction to Quantum Reinforcement Learning

A 20-min introduction to QRL presented in the the 15th International Conference on ICT Convergence - ICTC 2024.

Paper: https://arxiv.org/abs/2409.05846

Learning to Program Variational Quantum Circuits with Fast Weights

In this paper, I introduced a framework in which a neural network is trained to dynamically modify the parameters of a quantum neural network (QNN). This enables the QNN to learn temporal or sequential tasks without the requirements of recurrent neural networks.

Code: https://github.com/ycchen1989/Quantum_FWP

Paper: https://arxiv.org/abs/2402.17760

Online Seminar Recordings

Youtube Playlist: https://youtube.com/playlist?list=PLrvbZF_ZDn6vjRjb17U9wZbhvnVmOtvtb&si=AlO81WGJThNLRA_0

Advances in Hybrid Quantum-classical Machine Learning

Presented in April 27, 2024

Advances in hybrid quantum-classical ML

Presented in September 9, 2023

Advances in Hybrid Quantum-Classical Machine Learning

Presented in July 8, 2023

Hybrid Quantum-Classical Machine Learning and Applications

Presented in April 20, 2023

When Reinforcement Learning Meets Quantum Computing

Presented in January 26, 2023

Introduction to Hybrid Quantum-Classical Machine Learning with Applications

Presented in June 5, 2022

Reinforcement Learning in the Quantum Regime

Presented in March 25, 2022

Introduction of Quantum-Enhanced Machine Learning

Presented in August 21, 2021

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