activity
20222024
most citedOut-of-distribution Detection with Implicit Outlier Transformation

10 citations · 20 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CL20241 cited

MEDFuse: Multimodal EHR Data Fusion with Masked Lab-Test Modeling and Large Language Models

Thao Minh Nguyen Phan, Cong-Tinh Dao, Chenwei Wu +7

Electronic health records (EHRs) are multimodal by nature, consisting of structured tabular features like lab tests and unstructured clinical notes. In real-life clinical practice,…

cs.LG2024

On the Learnability of Out-of-distribution Detection

Zhen Fang, Yixuan Li, Feng Liu +2

Supervised learning aims to train a classifier under the assumption that training and test data are from the same distribution. To ease the above assumption, researchers have studi…

cs.CV20232 cited

Attacking Perceptual Similarity Metrics

Abhijay Ghildyal, Feng Liu

Perceptual similarity metrics have progressively become more correlated with human judgments on perceptual similarity; however, despite recent advances, the addition of an impercep…

cs.LG202310 cited

Out-of-distribution Detection with Implicit Outlier Transformation

Qizhou Wang, Junjie Ye, Feng Liu +5

Outlier exposure (OE) is powerful in out-of-distribution (OOD) detection, enhancing detection capability via model fine-tuning with surrogate OOD data. However, surrogate data typi…

cs.CV20226 cited

Neighborhood Collective Estimation for Noisy Label Identification and Correction

Jichang Li, Guanbin Li, Feng Liu +1

Learning with noisy labels (LNL) aims at designing strategies to improve model performance and generalization by mitigating the effects of model overfitting to noisy labels. The ke…

cs.LG20221 cited

Balanced Graph Structure Learning for Multivariate Time Series Forecasting

Weijun Chen, Yanze Wang, Chengshuo Du +3

Accurate forecasting of multivariate time series is an extensively studied subject in finance, transportation, and computer science. Fully mining the correlation and causation betw…