Gao, Yansong (髙岩🌲)

PhD Candidate,
GRASP Robotics Laboratory,
University of Pennsylvania
Philadelphia, USA
E-mail: gaoyans@sas.upenn.edu

About me

Hi! I am a Ph.D. Candidate at the University of Pennsylvania and advised by Pratik Chaudhari. I work on a handbook for pre-training models. My research interests span areas like pre-training, transfer learning, unsupervised learning, generative models, and information theory. I graduated from Shanghai Jiao Tong University (SJTU) in 2017 with a Dual Degree (Bachelor in Mathematics and Physics), where Yaokun Wu advised me.

Research

My research interests include:

Multi-task Learning, Transfer Learning, and Unsupervised Learning
Deep Gnerative Models, Foundation Models
Information Geometry, Information Theory
Algorithmic game theory

Current work

A handbook for pretraining learning models

Selected Publications

Fast Diffusion Probabilistic Model Sampling through the lens of Backward Error Analysis

Yansong Gao*, Zhihong Pan, Xin Zhou, Le Kang, and Pratik Chaudhari

[PDF]

In submission 2023
Deep Reference Priors: What is the best way to pretrain a model?

Yansong Gao*, Rahul Ramesh*, and Pratik Chaudhari

ICML 2022

[ArXiv][code]
Beyond the worst-case analysis of random priority: Smoothed and average-case approximation ratios in mechanism design

Xiaotie Deng, Yansong Gao, and Jie Zhang

Information and Computation 2022

[PDF]
An information-geometric distance on the space of tasks

Yansong Gao and Pratik Chaudhari

ICML 2021

[PDF][code]
A free-energy principle for representation learning

Yansong Gao and Pratik Chaudhari

ICML 2020

[PDF][code]
Average-case analysis of the assignment problem with independent preferences

Yansong Gao and Jie Zhang

IJCAI 2019

[PDF]
On Scheduling Mechanisms Beyond the Worst Case

Yansong Gao and Jie Zhang

[ArXiv]

Full list of publications in Google Scholar.

Reviewer

ICML2020, ICML2021, ICML2022, NeurIPS2021, NeurIPS2022, ICLR2022, Entropy