215 citations · 888 across the 37 of their papers we have counts for
5 papers · 1 filter
MTV: Visual Analytics for Detecting, Investigating, and Annotating Anomalies in Multivariate Time Series
Dongyu Liu, Sarah Alnegheimish, Alexandra Zytek +1
Detecting anomalies in time-varying multivariate data is crucial in various industries for the predictive maintenance of equipment. Numerous machine learning (ML) algorithms have b…
VBridge: Connecting the Dots Between Features and Data to Explain Healthcare Models
Furui Cheng, Dongyu Liu, Fan Du +5
Machine learning (ML) is increasingly applied to Electronic Health Records (EHRs) to solve clinical prediction tasks. Although many ML models perform promisingly, issues with model…
Meeting in the notebook: a notebook-based environment for micro-submissions in data science collaborations
Micah J. Smith, Jürgen Cito, Kalyan Veeramachaneni
Developers in data science and other domains frequently use computational notebooks to create exploratory analyses and prototype models. However, they often struggle to incorporate…
AQEyes: Visual Analytics for Anomaly Detection and Examination of Air Quality Data
Dongyu Liu, Kalyan Veeramachaneni, Alexander Geiger +2
Anomaly detection plays a key role in air quality analysis by enhancing situational awareness and alerting users to potential hazards. However, existing anomaly detection approache…
Sibyl: Understanding and Addressing the Usability Challenges of Machine Learning In High-Stakes Decision Making
Alexandra Zytek, Dongyu Liu, Rhema Vaithianathan +1
Machine learning (ML) is being applied to a diverse and ever-growing set of domains. In many cases, domain experts - who often have no expertise in ML or data science - are asked t…