activity
20162021
most citedA Convolutional Autoencoder for Multi-Subject fMRI Data Aggregation

22 citations · 40 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CG2021

Optimal Construction for Time-Convex Hull with Two Orthogonal Highways in the L1-metric

Jyun-Yu Chen, Po-Hsuan Chen

We consider the time-convex hull problem in the presence of two orthogonal highways H. In this problem, the travelling speed on the highway is faster than off the highway, and the…

cs.LG2018★ 11 cited

Shared Representational Geometry Across Neural Networks

Qihong Lu, Po-Hsuan Chen, Jonathan W. Pillow +3

Different neural networks trained on the same dataset often learn similar input-output mappings with very different weights. Is there some correspondence between these neural netwo…

q-bio.NC2016★ 1 cited

Mapping Between fMRI Responses to Movies and their Natural Language Annotations

Kiran Vodrahalli, Po-Hsuan Chen, Yingyu Liang +8

Several research groups have shown how to correlate fMRI responses to the meanings of presented stimuli. This paper presents new methods for doing so when only a natural language a…

stat.ML2016★ 6 cited

A Searchlight Factor Model Approach for Locating Shared Information in Multi-Subject fMRI Analysis

Hejia Zhang, Po-Hsuan Chen, Janice Chen +5

There is a growing interest in joint multi-subject fMRI analysis. The challenge of such analysis comes from inherent anatomical and functional variability across subjects. One appr…

stat.ML2016★ 22 cited

A Convolutional Autoencoder for Multi-Subject fMRI Data Aggregation

Po-Hsuan Chen, Xia Zhu, Hejia Zhang +5

Finding the most effective way to aggregate multi-subject fMRI data is a long-standing and challenging problem. It is of increasing interest in contemporary fMRI studies of human c…