8 citations · 9 across the 7 of their papers we have counts for
7 papers
Evidence-Guided Neural Architecture Selection under Uncertainty for Subject-Specific Blood Glucose Forecasting
Md Azharul Islam, Dwyer Deighan, Tarunraj Singha +1
Reliable neural architecture selection is an open challenge in time-series forecasting under limited, noisy, and heterogeneous data, where standard heuristic architecture design an…
Mixture of neural operator experts for learning boundary conditions and model selection
Dwyer Deighan, Jonas A. Actor, Ravi G. Patel
While Fourier-based neural operators are best suited to learning mappings between functions on periodic domains, several works have introduced techniques for incorporating non triv…
Stochastic Deep Learning Surrogate Models for Uncertainty Propagation in Microstructure-Properties of Ceramic Aerogels
Md Azharul Islam, Dwyer Deighan, Shayan Bhattacharjee +4
This study presents an integrated computational framework that, given synthesis parameters, predicts the resulting microstructural morphology and mechanical response of ceramic aer…
Physics Informed Machine Learning for Chemistry Tabulation
Amol Salunkhe, Dwyer Deighan, Paul Desjardin +1
Modeling of turbulent combustion system requires modeling the underlying chemistry and the turbulent flow. Solving both systems simultaneously is computationally prohibitive. Inste…
ChemTab: A Physics Guided Chemistry Modeling Framework
Amol Salunkhe, Dwyer Deighan, Paul DesJardin +1
Modeling of turbulent combustion system requires modeling the underlying chemistry and the turbulent flow. Solving both systems simultaneously is computationally prohibitive. Inste…
Genetic-algorithm-optimized neural networks for gravitational wave classification
Dwyer S. Deighan, Scott E. Field, Collin D. Capano +1
Gravitational-wave detection strategies are based on a signal analysis technique known as matched filtering. Despite the success of matched filtering, due to its computational cost…
Mining Spatio-temporal Data on Industrialization from Historical Registries
David Berenbaum, Dwyer Deighan, Thomas Marlow +3
Despite the growing availability of big data in many fields, historical data on socioevironmental phenomena are often not available due to a lack of automated and scalable approach…