Damien Jian

Email:
f10245023@ntu.edu.tw damien.jian.research@gmail.com

Hi there, this is Damien Jian (簡大閔 in Chinese, pronounced like Jian Da-Min). I’m a PhD student of Graduate Institute of Applied Physics under the guidance of Prof. Hsi-Sheng Goan at National Taiwan University.

I am interested in quantum machine learning, including but not limited to model design, training methods, and theoretical analysis. I am excited to work on discovering and exploring the quantum advantages of quantum computers in machine learning over classical machine learning.

I’m working on customizing these pages right now. It will soon looks better.

“Do not go gentle into that good night.”

— From the movie Interstellar

selected publications

ArXiv
Test-Time Training with Quantum Auto-Encoder: From Distribution Shift to Noisy Quantum Circuits

Damien Jian^*, Yu-Chao Huang^*, and Hsi-Sheng Goan

arXiv preprint arXiv:2411.06828, 2024

* These authors contributed equally to this work

Abs arXiv Bib Website

In this paper, we propose test-time training with the quantum auto-encoder (QTTT). QTTT adapts to (1) data distribution shifts between training and testing data and (2) quantum circuit error by minimizing the self-supervised loss of the quantum auto-encoder. Empirically, we show that QTTT is robust against data distribution shifts and effective in mitigating random unitary noise in the quantum circuits during the inference. Additionally, we establish the theoretical performance guarantee of the QTTT architecture. Our novel framework presents a significant advancement in developing quantum neural networks for future real-world applications and functions as a plug-and-play extension for quantum machine learning models.
@article{jian2024qttt, title = {Test-Time Training with Quantum Auto-Encoder: From Distribution Shift to Noisy Quantum Circuits}, author = {Jian, Damien and Huang, Yu-Chao and Goan, Hsi-Sheng}, note = {* These authors contributed equally to this work}, journal = {arXiv preprint arXiv:2411.06828}, year = {2024}, }