4 citations · 7 across the 4 of their papers we have counts for
4 papers
One-hot Generalized Linear Model for Switching Brain State Discovery
Chengrui Li, Soon Ho Kim, Chris Rodgers +2
Exposing meaningful and interpretable neural interactions is critical to understanding neural circuits. Inferred neural interactions from neural signals primarily reflect functiona…
Infer and Adapt: Bipedal Locomotion Reward Learning from Demonstrations via Inverse Reinforcement Learning
Feiyang Wu, Zhaoyuan Gu, Hanran Wu +2
Enabling bipedal walking robots to learn how to maneuver over highly uneven, dynamically changing terrains is challenging due to the complexity of robot dynamics and interacted env…
JGAT: a joint spatio-temporal graph attention model for brain decoding
Han Yi Chiu, Liang Zhao, Anqi Wu
The decoding of brain neural networks has been an intriguing topic in neuroscience for a well-rounded understanding of different types of brain disorders and cognitive stimuli. Int…
Inverse Reinforcement Learning with the Average Reward Criterion
Feiyang Wu, Jingyang Ke, Anqi Wu
We study the problem of Inverse Reinforcement Learning (IRL) with an average-reward criterion. The goal is to recover an unknown policy and a reward function when the agent only ha…