Author

Jacob Hauck

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#machine learning Preprint Jul 2025

Discretization-independent operator learning for partial differential equations

A new and general encode-approximate-reconstruct operator learning model that leverages learned neural representations of bases for input and output function distributions that is discretization-independent, making it particularly effective for multiresolution learning.

Jacob Hauck, Yanzhi Zhang · 0 citations

#generative ai Preprint Sep 2026

Score-Based Generative Data Assimilation for Integrating Aggregated Surveillance Data into Agent-Based Models in Epidemic Tracking

A generative AI-based data-assimilation framework for partially observed epidemic ABMs that estimates both the epidemic state and a heterogeneous parameter field while respecting the gap between observable macrostates and latent agent-level microstates is developed.

Si-Ming Liang, Jacob Hauck, Ming-Lei Yang et al. · 0 citations