activity
20192022
most citedDrug-Target Interaction Prediction with Graph Attention networks

18 citations · 23 across the 4 of their papers we have counts for

collaborators

6 papers

cs.LG20222 cited

Uncertainty in Extreme Multi-label Classification

Jyun-Yu Jiang, Wei-Cheng Chang, Jiong Zhong +2

Uncertainty quantification is one of the most crucial tasks to obtain trustworthy and reliable machine learning models for decision making. However, most research in this domain ha…

cs.SI2021

#StayHome or #Marathon? Social Media Enhanced Pandemic Surveillance on Spatial-temporal Dynamic Graphs

Yichao Zhou, Jyun-yu Jiang, Xiusi Chen +1

COVID-19 has caused lasting damage to almost every domain in public health, society, and economy. To monitor the pandemic trend, existing studies rely on the aggregation of traditi…

q-bio.QM202118 cited

Drug-Target Interaction Prediction with Graph Attention networks

Haiyang Wang, Guangyu Zhou, Siqi Liu +2

Motivation: Predicting Drug-Target Interaction (DTI) is a well-studied topic in bioinformatics due to its relevance in the fields of proteomics and pharmaceutical research. Althoug…

cs.AI2020

Long Document Ranking with Query-Directed Sparse Transformer

Jyun-Yu Jiang, Chenyan Xiong, Chia-Jung Lee +1

The computing cost of transformer self-attention often necessitates breaking long documents to fit in pretrained models in document ranking tasks. In this paper, we design Query-Di…

cs.CL20203 cited

"The Boating Store Had Its Best Sail Ever": Pronunciation-attentive Contextualized Pun Recognition

Yichao Zhou, Jyun-Yu Jiang, Jieyu Zhao +2

Humor plays an important role in human languages and it is essential to model humor when building intelligence systems. Among different forms of humor, puns perform wordplay for hu…

cs.CL2019

Learning to Discriminate Perturbations for Blocking Adversarial Attacks in Text Classification

Yichao Zhou, Jyun-Yu Jiang, Kai-Wei Chang +1

Adversarial attacks against machine learning models have threatened various real-world applications such as spam filtering and sentiment analysis. In this paper, we propose a novel…