5 papers · 1 filter
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…
Agentic Framework for Epidemiological Modeling
Rituparna Datta, Zihan Guan, Baltazar Espinoza +5
Epidemic modeling is essential for public health planning, yet traditional approaches rely on fixed model classes that require manual redesign as pathogens, policies, and scenario…
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…