9 papers
EpiNarrate: Agentic Generation of Grounded Narratives from Epidemiological Scenario Projections
Rituparna Datta, Srini Venkatramanan, Bryan L. Lewis +6
Generation of clear and accessible public health narratives is critical for communicating complex epidemiological projections to policymakers and the general public at large. Such…
IUU+DB: Tracking Illegal, Unreported, and Unregulated Fishing, Seafood Fraud, and Labor Abuse through LLM-driven Information Extraction
Henry Bodwell, Hong Yang, John C. Simeone +7
Illegal, unreported, and unregulated fishing (IUU) traditionally refers to fishing activities that violate applicable laws or occur in areas that lack applicable laws. We propose t…
How (Not) to Hybridize Neural and Mechanistic Models for Epidemiological Forecasting
Yiqi Su, Ray Lee, Jiaming Cui +1
Epidemiological forecasting from surveillance data is a hard problem and hybridizing mechanistic compartmental models with neural models is a natural direction. The mechanistic str…
LLM-ACES: Closed-Loop Discovery of Dynamical Systems with LLM-Guided Adaptive Search
Nikhil Abhyankar, Sha Li, Sanchit Kabra +3
Recovering governing Ordinary Differential Equations (ODEs) from data is a central challenge in modeling dynamical systems across scientific domains. Existing approaches cast disco…
Toward World Models for Epidemiology
Zeeshan Memon, Yiqi Su, Christo Kurisummoottil Thomas +3
World models have emerged as a unifying paradigm for learning latent dynamics, simulating counterfactual futures, and supporting planning under uncertainty. In this paper, we argue…
An Invariant Compiler for Neural ODEs in AI-Accelerated Scientific Simulation
Fangzhou Yu, Yiqi Su, Ray Lee +2
Neural ODEs are increasingly used as continuous-time models for scientific and sensor data, but unconstrained neural ODEs can drift and violate domain invariants (e.g., conservatio…