Xinyang Liu (刘昕洋)
Master student
School of Electronic Engineering
Xidian University
Email: lxy771258012 [AT] 163 [dot] com
Google scholar | Github | Twitter
Bio
Howdy! I am currently a final-year Master student in the School of Electronic Engineering, Xidian University, advised by Prof. Bo Chen. And I am also advised by Prof. Mingyuan Zhou, an Associate Professor and Curtis Mathes Memorial Fellow at the University of Texas at Austin. Previously, I obtained my bachelor’s degree from Xidian University in 2021.
My research interests lie in the general area of machine learning, particularly in probabilistic inference and deep learning. My recent researches focus on Generative Modeling and Representation Learning as well as their applications in image generation, text analysis, graph learning and transfer learning.
I’m looking for PhD 25 Fall!
Welcome collaboration about Generative AI and Multi/Cross-Modal Representation Learning anytime!
news
Dec 3, 2024 | Our paper “MolGuide: 2D Molecular Optimization with Preserved Structural Motifs Guidance” is accepted by the workshop AAAI 2024: LLMs4Bio. It’s my first attempt at “Graph Generation”, where we are doing something new under this topic, please stay tuned! |
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Sep 23, 2023 | Two papers are accepted by NeurIPS 2023! |
Apr 27, 2023 | Our paper “Bayesian Progressive Deep Topic Model with Knowledge Informed Textual Data Coarsening Process” is accepted by ICML 2023. |
Feb 15, 2023 | We have open sourced a new version of PyDPM, and welcome to join the open source library of deep probabilistic models! PyDPM is a python library focuses on constructing Deep Probabilistic Models (DPMs). Our developed Pydpm not only provides efficient distribution sampling functions on GPU, but also has included the implementations of existing popular DPMs. |