3 citations · 6 across the 5 of their papers we have counts for
5 papers
A Theoretical Analysis of Discrete Flow Matching Generative Models
Maojiang Su, Mingcheng Lu, Jerry Yao-Chieh Hu +4
We provide a theoretical analysis for end-to-end training Discrete Flow Matching (DFM) generative models. DFM is a promising discrete generative modeling framework that learns the…
NdLinear: Preserving Multi-Dimensional Structure for Parameter-Efficient Neural Networks
Alex Reneau, Jerry Yao-Chieh Hu, Zhongfang Zhuang +6
In deep learning, processing multidimensional inputs (e.g., images, medical scans, and time series) is an important task that often requires flattening the inputs. We introduce $\m…
Differentially Private Kernel Density Estimation
Erzhi Liu, Jerry Yao-Chieh Hu, Alex Reneau +2
We introduce a refined differentially private (DP) data structure for kernel density estimation (KDE), offering not only improved privacy-utility tradeoff but also better efficienc…
Feature Programming for Multivariate Time Series Prediction
Alex Reneau, Jerry Yao-Chieh Hu, Chenwei Xu +3
We introduce the concept of programmable feature engineering for time series modeling and propose a feature programming framework. This framework generates large amounts of predict…
Supporting User Autonomy with Multimodal Fusion to Detect when a User Needs Assistance from a Social Robot
Alex Reneau, Jason R. Wilson
It is crucial for any assistive robot to prioritize the autonomy of the user. For a robot working in a task setting to effectively maintain a user's autonomy it must provide timely…