14 citations · 19 across the 4 of their papers we have counts for
3 papers · 1 filter
Improved Structural Discovery and Representation Learning of Multi-Agent Data
Jennifer Hobbs, Matthew Holbrook, Nathan Frank +2
Central to all machine learning algorithms is data representation. For multi-agent systems, selecting a representation which adequately captures the interactions among agents is ch…
Rugby-Bot: Utilizing Multi-Task Learning & Fine-Grained Features for Rugby League Analysis
Matthew Holbrook, Jennifer Hobbs, Patrick Lucey
Sporting events are extremely complex and require a multitude of metrics to accurate describe the event. When making multiple predictions, one should make them from a single source…
Generating Multi-Agent Trajectories using Programmatic Weak Supervision
Eric Zhan, Stephan Zheng, Yisong Yue +2
We study the problem of training sequential generative models for capturing coordinated multi-agent trajectory behavior, such as offensive basketball gameplay. When modeling such s…