11 citations · 15 across the 4 of their papers we have counts for
4 papers
Vision-language models for decoding provider attention during neonatal resuscitation
Felipe Parodi, Jordan Matelsky, Alejandra Regla-Vargas +6
Neonatal resuscitations demand an exceptional level of attentiveness from providers, who must process multiple streams of information simultaneously. Gaze strongly influences decis…
A large language model-assisted education tool to provide feedback on open-ended responses
Jordan K. Matelsky, Felipe Parodi, Tony Liu +2
Open-ended questions are a favored tool among instructors for assessing student understanding and encouraging critical exploration of course material. Providing feedback for such r…
Exploiting Large Neuroimaging Datasets to Create Connectome-Constrained Approaches for more Robust, Efficient, and Adaptable Artificial Intelligence
Erik C. Johnson, Brian S. Robinson, Gautam K. Vallabha +17
Despite the progress in deep learning networks, efficient learning at the edge (enabling adaptable, low-complexity machine learning solutions) remains a critical need for defense a…
Scatterbrained: A flexible and expandable pattern for decentralized machine learning
Miller Wilt, Jordan K. Matelsky, Andrew S. Gearhart
Federated machine learning is a technique for training a model across multiple devices without exchanging data between them. Because data remains local to each compute node, federa…