4 citations · 7 across the 3 of their papers we have counts for
3 papers
Skull stripping with purely synthetic data
Jong Sung Park, Juhyung Ha, Siddhesh Thakur +3
While many skull stripping algorithms have been developed for multi-modal and multi-species cases, there is still a lack of a fundamentally generalizable approach. We present PUMBA…
Learning sources of variability from high-dimensional observational studies
Eric W. Bridgeford, Jaewon Chung, Brian Gilbert +6
Causal inference studies whether the presence of a variable influences an observed outcome. As measured by quantities such as the "average treatment effect," this paradigm is emplo…
Discovering the Signal Subgraph: An Iterative Screening Approach on Graphs
Cencheng Shen, Shangsi Wang, Alexandra Badea +2
Supervised learning on graphs is a challenging task due to the high dimensionality and inherent structural dependencies in the data, where each edge depends on a pair of vertices.…