1 code implementation • NeurIPS 2021 • Dweep Trivedi, Jesse Zhang, Shao-Hua Sun, Joseph J. Lim
To alleviate the difficulty of learning to compose programs to induce the desired agent behavior from scratch, we propose to first learn a program embedding space that continuously parameterizes diverse behaviors in an unsupervised manner and then search over the learned program embedding space to yield a program that maximizes the return for a given task.
1 code implementation • NeurIPS 2020 • Nitin Kamra, Hao Zhu, Dweep Trivedi, Ming Zhang, Yan Liu
Trajectory prediction for scenes with multiple agents and entities is a challenging problem in numerous domains such as traffic prediction, pedestrian tracking and path planning.