129 citations · 292 across the 10 of their papers we have counts for
10 papers
Bayesian Modeling and Prediction of Generalized Contact Matrices
Shozen Dan, David A. van Dyk, Zhi Ling +2
Social contact matrices are essential tools in infectious disease epidemiology as they quantify close-range human contact patterns which directly drive the transmission of airborne…
medR: Reward Engineering for Clinical Offline Reinforcement Learning via Tri-Drive Potential Functions
Qianyi Xu, Gousia Habib, Feng Wu +5
Reinforcement Learning (RL) offers a powerful framework for optimizing dynamic treatment regimes (DTRs). However, clinical RL is fundamentally bottlenecked by reward engineering: t…
Toward Clinically Explainable AI for Medical Diagnosis: A Foundation Model with Human-Compatible Reasoning via Reinforcement Learning
Qika Lin, Yifan Zhu, Bin Pu +14
The clinical adoption of artificial intelligence (AI) in medical diagnostics is critically hampered by its black-box nature, which prevents clinicians from verifying the rationale…
Evidential time-to-event prediction with calibrated uncertainty quantification
Ling Huang, Yucheng Xing, Swapnil Mishra +2
Time-to-event analysis provides insights into clinical prognosis and treatment recommendations. However, this task is more challenging than standard regression problems due to the…
Uncertainty-Aware Regression for Socio-Economic Estimation via Multi-View Remote Sensing
Fan Yang, Sahoko Ishida, Mengyan Zhang +4
Remote sensing imagery offers rich spectral data across extensive areas for Earth observation. Many attempts have been made to leverage these data with transfer learning to develop…
Towards pandemic preparedness: ability to estimate high-resolution social contact patterns from longitudinal surveys
Shozen Dan, Joshua Tegegne, Yu Chen +5
Social contact surveys are an important tool to assess infection risks within populations, and the effect of non-pharmaceutical interventions on social behaviour during disease out…
Modeling Popularity in Asynchronous Social Media Streams with Recurrent Neural Networks
Swapnil Mishra, Marian-Andrei Rizoiu, Lexing Xie
Understanding and predicting the popularity of online items is an important open problem in social media analysis. Considerable progress has been made recently in data-driven predi…
SIR-Hawkes: Linking Epidemic Models and Hawkes Processes to Model Diffusions in Finite Populations
Marian-Andrei Rizoiu, Swapnil Mishra, Quyu Kong +2
Among the statistical tools for online information diffusion modeling, both epidemic models and Hawkes point processes are popular choices. The former originate from epidemiology,…
A Tutorial on Hawkes Processes for Events in Social Media
Marian-Andrei Rizoiu, Young Lee, Swapnil Mishra +1
This chapter provides an accessible introduction for point processes, and especially Hawkes processes, for modeling discrete, inter-dependent events over continuous time. We start…
Feature Driven and Point Process Approaches for Popularity Prediction
Swapnil Mishra, Marian-Andrei Rizoiu, Lexing Xie
Predicting popularity, or the total volume of information outbreaks, is an important subproblem for understanding collective behavior in networks. Each of the two main types of rec…