32 citations · 43 across the 7 of their papers we have counts for
8 papers
From Graphs to Feeders: Constraint-Guided Diffusion for Rule-Compliant Feeder Generation
Yu Qin, Andrew Glaws, Aadil Latif +1
Generative modeling approaches often focus on recovering broad statistical characteristics from the training data. In the context of graph generation, this may refer to degree dist…
Position: AI Agents in Scientific Teams Should Be Studied as Human-Agent Systems
Patrick Emami, Sameera Horawalavithana, Truc Nguyen +11
Large language model-based agents are increasingly deployed as collaborators in scientific discovery yet most current work focuses on the autonomous capabilities of "AI Scientists"…
Conditional Distribution Estimation of Building Characteristics with Diffusion Models for Urban Energy Modeling
Saumya Sinha, Alexandre Cortiella, Rawad El Kontar +3
Understanding current energy consumption behavior in communities is critical for informing future energy use decisions and enabling efficient energy management. Urban energy models…
Super Resolution for Renewable Energy Resource Data With Wind From Reanalysis Data and Application to Ukraine
Brandon N. Benton, Grant Buster, Pavlo Pinchuk +4
With a potentially increasing share of the electricity grid relying on wind to provide generating capacity and energy, there is an expanding global need for historically accurate,…
Physics-Driven Convolutional Autoencoder Approach for CFD Data Compressions
Alberto Olmo, Ahmed Zamzam, Andrew Glaws +1
With the growing size and complexity of turbulent flow models, data compression approaches are of the utmost importance to analyze, visualize, or restart the simulations. Recently,…
GANISP: a GAN-assisted Importance SPlitting Probability Estimator
Malik Hassanaly, Andrew Glaws, Ryan N. King
Designing manufacturing processes with high yield and strong reliability relies on effective methods for rare event estimation. Genealogical importance splitting reduces the varian…
Adversarial sampling of unknown and high-dimensional conditional distributions
Malik Hassanaly, Andrew Glaws, Karen Stengel +1
Many engineering problems require the prediction of realization-to-realization variability or a refined description of modeled quantities. In that case, it is necessary to sample e…
A Unified Architecture for Data-Driven Metadata Tagging of Building Automation Systems
Sakshi Mishra, Andrew Glaws, Dylan Cutler +4
This article presents a Unified Architecture for automated point tagging of Building Automation System data, based on a combination of data-driven approaches. Advanced energy analy…