Guan-Horng Liu
Machine Learning PhD @ Georgia Tech 🚀

Hi, I am Guan-Horng Liu (I go by "Guan" ), a fourth-year Machine Learning PhD in Georgia Tech advised by Evangelos A. Theodorou. I also work closely with Molei Tao from Georgia Tech and Valentin De Bortoli from CNRS.
My research concerns scalable computational methods for neural dynamics, including Neural ODEs, Neural SDEs (e.g., diffusion models), DNNs (as discrete-time systems), their mean-field extensions, and etc. These neural dynamics pose interesting numerical challenges to traditional computational methods. In return, studies from dynamic and control standpoints have inspired new machine learning pipelines in principled algorithmic design and development of theoretical insights grounded on optimal control, stochastic processes, game theory, dynamic optimal transport, and statistical physics. This new line of research has received spotlight/oral presentations in ICLR’21, ICML’21, NeurIPS’21, and NeurIPS’22.
I am fortunate to work in Nvidia Research during 2022 Summer, developing robust diffusion models with Weili Nie, Arash Vahdat, De-An Huang, and Anima Anandkumar. See my full CV here (updated in Nov 2022).
Contact:
ghliu [at] gatech [dot] edu
Follow:
Google Scholar
|
LinkedIn
|
ghliu
|
@guanhorng_liu
Updates
Nov, 2022 |
![]() |
---|---|
Oct, 2022 |
![]() |
Sep, 2022 |
![]() |
Jun, 2022 |
![]() |
Feb, 2022 |
![]() |
Jan, 2022 |
![]() |
Dec, 2021 |
![]() |
Oct, 2021 |
![]() |
Sep, 2021 |
![]() |
May, 2021 |
![]() |
Jan, 2021 |
![]() |