
Cornell University Artificial Intelligence (CUAI)
Undergraduate ML research
and education.
Overview
Cornell University Artificial Intelligence (CUAI) focuses on undergraduate
machine learning research and publication.
Our primary efforts are described below:
Research Group
The group will work closely with the club's officers to aim for a publication at a top ML
conference (NeurIPS, ICML, etc.). People that have experience will be a good fit, as we will hit the
ground running. We encourage people from a diverse background.
Apply
here. See examples of our publications here.
Reading Group
We will meet weekly to discuss papers (and research in general) in the field of machine
learning. The goal is to familiarize
people with state-of-the-art research. This is meant for students with some experience, as we will
be closely following recent literature.
Research Group Applications
Update: Application for Fall 2022 is now closed!
Publications

Riemannian Residual Neural Networks Isay Katsman*, Eric M. Chen*, Sidhanth Holalkere*, Anna Asch*, Aaron Lou, Ser-Nam Lim Christopher De Sa

GAPX: Generalized Autoregressive Paraphrase Identification
Yifei Zhou, Renyu Li, Hayden Housen, Ser-Nam Lim
NeurIPS 2022.

Equivariant Manifold Flows
Isay Katsman*, Aaron Lou*, Derek Lim*, Qingxuan Jiang*, Ser-Nam Lim, Christopher De
Sa
NeurIPS 2021

Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods
Derek Lim*, Felix Hohne*, Xiuyu Li*, Sijia Linda Huang, Vaishnavi Gupta, Omkar Bhalerao, Ser-Nam Lim
NeurIPS 2021

Combining Label Propagation and Simple Models Out-performs Graph Neural Networks
Qian Huang*, Horace He*, Abhay Singh, Ser-Nam Lim, Austin Benson
ICLR 2021

Neural Manifold Ordinary Differential Equations
Aaron Lou*, Derek Lim*, Isay Katsman*, Leo Huang*, Qingxuan Jiang, Ser-Nam
Lim,
Christopher De Sa
NeurIPS 2020

Better Set Representations For Relational Reasoning
Qian Huang*, Horace He*, Abhay Singh, Yan Zhang, Ser-Nam Lim, Austin Benson
NeurIPS 2020

Differentiating through the Fréchet Mean
Aaron Lou*, Isay Katsman*, Qingxuan Jiang*, Serge Belongie, Ser-Nam Lim, Christopher
De Sa
ICML 2020

Enhancing Adversarial Example Transferability with an Intermediate Level Attack
Qian Huang*, Isay Katsman*, Horace He*, Zeqi Gu*, Serge Belongie, Ser-Nam Lim
ICCV 2019

Adversarial Example Decomposition
Horace He, Aaron Lou*, Qingxuan Jiang*, Isay Katsman*, Serge Belongie, Ser-Nam Lim
ICML 2019 Workshop, Security and Privacy of Machine Learning
*indicates equal contribution