66 citations · 188 across the 20 of their papers we have counts for
5 papers · 1 filter
End-to-End Stochastic Optimization with Energy-Based Model
Lingkai Kong, Jiaming Cui, Yuchen Zhuang +3
Decision-focused learning (DFL) was recently proposed for stochastic optimization problems that involve unknown parameters. By integrating predictive modeling with an implicitly di…
Data-Centric Epidemic Forecasting: A Survey
Alexander Rodríguez, Harshavardhan Kamarthi, Pulak Agarwal +4
The COVID-19 pandemic has brought forth the importance of epidemic forecasting for decision makers in multiple domains, ranging from public health to the economy as a whole. While…
Differentiable Agent-based Epidemiology
Ayush Chopra, Alexander Rodríguez, Jayakumar Subramanian +4
Mechanistic simulators are an indispensable tool for epidemiology to explore the behavior of complex, dynamic infections under varying conditions and navigate uncertain environment…
When Rigidity Hurts: Soft Consistency Regularization for Probabilistic Hierarchical Time Series Forecasting
Harshavardhan Kamarthi, Lingkai Kong, Alexander Rodríguez +2
Probabilistic hierarchical time-series forecasting is an important variant of time-series forecasting, where the goal is to model and forecast multivariate time-series that have un…
EINNs: Epidemiologically-informed Neural Networks
Alexander Rodríguez, Jiaming Cui, Naren Ramakrishnan +2
We introduce EINNs, a framework crafted for epidemic forecasting that builds upon the theoretical grounds provided by mechanistic models as well as the data-driven expressibility a…