3 citations · 4 across the 3 of their papers we have counts for
3 papers
Memory-based gaze prediction in deep imitation learning for robot manipulation
Heecheol Kim, Yoshiyuki Ohmura, Yasuo Kuniyoshi
Deep imitation learning is a promising approach that does not require hard-coded control rules in autonomous robot manipulation. The current applications of deep imitation learning…
Macro Action Reinforcement Learning with Sequence Disentanglement using Variational Autoencoder
Heecheol Kim, Masanori Yamada, Kosuke Miyoshi +1
One problem in the application of reinforcement learning to real-world problems is the curse of dimensionality on the action space. Macro actions, a sequence of primitive actions,…
FAVAE: Sequence Disentanglement using Information Bottleneck Principle
Masanori Yamada, Heecheol Kim, Kosuke Miyoshi +1
We propose the factorized action variational autoencoder (FAVAE), a state-of-the-art generative model for learning disentangled and interpretable representations from sequential da…