Xinyang Liu (刘昕洋)
Master student
School of Electronic Engineering
Xidian University
Email: xinyangATK [AT] gmail [dot] com
Google scholar | Github | Twitter
Bio
Howdy! I am a research intern at Purdue University, advised by Prof. Ruqi Zhang. I’m also work closely with Prof. Mingyuan Zhou, an Associate Professor at the University of Texas at Austin. I received my M.S degree from Xidian University in 2024, advised by Prof. Bo Chen. Previously, I obtained my B.S degree from Xidian University in 2021.
My research interests lie in the general area of machine learning, particularly in solving practical problems through advanced Generative AI systems. My recent researches focus on Generative Modeling, including its theoretical exploration and various applications in data generation and multi/cross-modal learning.
Now I’m looking for PhD 25 Fall and here is my CV !
In addition, I am very interested in robot learning, planning, and AI4Science within the framework of Generative AI.
If you share the same research interests with me, feel free to reach out or add my WeChat.
news
Jun, 2024 | I graduated with a master’s degree in Xidian University! |
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Apr, 2024 | Our paper “Patch-Prompt Aligned Bayesian Prompt Tuning for Vision-Language Models” is accepted by UAI 2024. |
Sep, 2023 | Two papers are accepted by NeurIPS 2023! |
Apr, 2023 | Our paper “Bayesian Progressive Deep Topic Model with Knowledge Informed Textual Data Coarsening Process” is accepted by ICML 2023. |
Feb, 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. |
selected publications
(*) denotes equal contribution