8 citations · 17 across the 4 of their papers we have counts for
6 papers
Revisiting Attention Weights as Explanations from an Information Theoretic Perspective
Bingyang Wen, K. P. Subbalakshmi, Fan Yang
Attention mechanisms have recently demonstrated impressive performance on a range of NLP tasks, and attention scores are often used as a proxy for model explainability. However, th…
Learning Models for Suicide Prediction from Social Media Posts
Ning Wang, Fan Luo, Yuvraj Shivtare +4
We propose a deep learning architecture and test three other machine learning models to automatically detect individuals that will attempt suicide within (1) 30 days and (2) six mo…
Causal-TGAN: Generating Tabular Data Using Causal Generative Adversarial Networks
Bingyang Wen, Luis Oliveros Colon, K. P. Subbalakshmi +1
Synthetic data generation becomes prevalent as a solution to privacy leakage and data shortage. Generative models are designed to generate a realistic synthetic dataset, which can…
Explainable Rumor Detection using Inter and Intra-feature Attention Networks
Mingxuan Chen, Ning Wang, K. P. Subbalakshmi
With social media becoming ubiquitous, information consumption from this media has also increased. However, one of the serious problems that have emerged with this increase, is the…
Explainable CNN-attention Networks (C-Attention Network) for Automated Detection of Alzheimer's Disease
Ning Wang, Mingxuan Chen, K. P. Subbalakshmi
In this work, we propose three explainable deep learning architectures to automatically detect patients with Alzheimer`s disease based on their language abilities. The architecture…
Personalized Early Stage Alzheimer's Disease Detection: A Case Study of President Reagan's Speeches
Ning Wang, Fan Luo, Vishal Peddagangireddy +2
Alzheimer`s disease (AD)-related global healthcare cost is estimated to be $1 trillion by 2050. Currently, there is no cure for this disease; however, clinical studies show that ea…