2 citations · 2 across the 2 of their papers we have counts for
2 papers
cs.LG2021★ 2 cited
Learning interaction rules from multi-animal trajectories via augmented behavioral models
Keisuke Fujii, Naoya Takeishi, Kazushi Tsutsui +10
Extracting the interaction rules of biological agents from movement sequences pose challenges in various domains. Granger causality is a practical framework for analyzing the inter…
cs.CV2019
Improved Activity Forecasting for Generating Trajectories
Daisuke Ogawa, Toru Tamaki, Tsubasa Hirakawa +3
An efficient inverse reinforcement learning for generating trajectories is proposed based of 2D and 3D activity forecasting. We modify reward function with norm and propose c…