1 citations · 2 across the 5 of their papers we have counts for
5 papers
Generating Synthetic Behavioral Populations from XR Motion
Xiaozheng Wang, Ryan P. McMahan
Large-scale behavioral datasets are becoming increasingly important for machine learning, personalization, and behavioral modeling in extended reality (XR). However, collecting XR…
The Capturing and Logging Ecological Virtual Experiences and Reality (CLEVER) - Job Simulator Dataset
Qidi J. Wang, Xiaozheng Wang, Akhilesh M. Anand +3
Virtual reality (VR) motion tracking and interaction data has become increasingly recognized as valuable for machine learning experiments for a variety of purposes, including predi…
Motion-Based User Identification across XR and Metaverse Applications by Deep Classification and Similarity Learning
Lukas Schach, Christian Rack, Ryan P. McMahan +1
This paper examines the generalization capacity of two state-of-the-art classification and similarity learning models in reliably identifying users based on their motions in variou…
QISCIT: A validated concept inventory assessment for quantum information science
Kelley Durkin, Manshuo Lin, Michael H. Kolodrubetz +1
Quantum information science (QIS) is a critical interdisciplinary field that requires a well-educated workforce in the near future. Numerous researchers and educators have been act…
RecolorCloud: A Point Cloud Tool for Recoloring, Segmentation, and Conversion
Esteban Segarra Martinez, Ryan P. McMahan
Point clouds are a 3D space representation of an environment that was recorded with a high precision laser scanner. These scanners can suffer from environmental interference such a…