855 citations · 2.1k across the 21 of their papers we have counts for
12 papers · 1 filter
Interpretable Artificial Intelligence through the Lens of Feature Interaction
Michael Tsang, James Enouen, Yan Liu
Interpretation of deep learning models is a very challenging problem because of their large number of parameters, complex connections between nodes, and unintelligible feature repr…
MIMIC-IF: Interpretability and Fairness Evaluation of Deep Learning Models on MIMIC-IV Dataset
Chuizheng Meng, Loc Trinh, Nan Xu +1
The recent release of large-scale healthcare datasets has greatly propelled the research of data-driven deep learning models for healthcare applications. However, due to the nature…
Physics-aware Spatiotemporal Modules with Auxiliary Tasks for Meta-Learning
Sungyong Seo, Chuizheng Meng, Sirisha Rambhatla +1
Modeling the dynamics of real-world physical systems is critical for spatiotemporal prediction tasks, but challenging when data is limited. The scarcity of real-world data and the…
Extracting Interpretable Concept-Based Decision Trees from CNNs
Conner Chyung, Michael Tsang, Yan Liu
In an attempt to gather a deeper understanding of how convolutional neural networks (CNNs) reason about human-understandable concepts, we present a method to infer labeled concept…
D-City: A Large-Scale Dashcam Video Dataset of Diverse Traffic Scenarios
Zhengping Che, Guangyu Li, Tracy Li +7
Driving datasets accelerate the development of intelligent driving and related computer vision technologies, while substantial and detailed annotations serve as fuels and powers to…
Benchmark of Deep Learning Models on Large Healthcare MIMIC Datasets
Sanjay Purushotham, Chuizheng Meng, Zhengping Che +1
Deep learning models (aka Deep Neural Networks) have revolutionized many fields including computer vision, natural language processing, speech recognition, and is being increasingl…
Boosting Deep Learning Risk Prediction with Generative Adversarial Networks for Electronic Health Records
Zhengping Che, Yu Cheng, Shuangfei Zhai +2
The rapid growth of Electronic Health Records (EHRs), as well as the accompanied opportunities in Data-Driven Healthcare (DDH), has been attracting widespread interests and attenti…
Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting
Yaguang Li, Rose Yu, Cyrus Shahabi +1
Spatiotemporal forecasting has various applications in neuroscience, climate and transportation domain. Traffic forecasting is one canonical example of such learning task. The task…
CSI: A Hybrid Deep Model for Fake News Detection
Natali Ruchansky, Sungyong Seo, Yan Liu
The topic of fake news has drawn attention both from the public and the academic communities. Such misinformation has the potential of affecting public opinion, providing an opport…
Exploiting Convolutional Neural Network for Risk Prediction with Medical Feature Embedding
Zhengping Che, Yu Cheng, Zhaonan Sun +1
The widespread availability of electronic health records (EHRs) promises to usher in the era of personalized medicine. However, the problem of extracting useful clinical representa…
Learning from Multiway Data: Simple and Efficient Tensor Regression
Rose Yu, Yan Liu
Tensor regression has shown to be advantageous in learning tasks with multi-directional relatedness. Given massive multiway data, traditional methods are often too slow to operate…
Recurrent Neural Networks for Multivariate Time Series with Missing Values
Zhengping Che, Sanjay Purushotham, Kyunghyun Cho +2
Multivariate time series data in practical applications, such as health care, geoscience, and biology, are characterized by a variety of missing values. In time series prediction a…