11 citations · 12 across the 4 of their papers we have counts for
4 papers
iPUNet:Iterative Cross Field Guided Point Cloud Upsampling
Guangshun Wei, Hao Pan, Shaojie Zhuang +2
Point clouds acquired by 3D scanning devices are often sparse, noisy, and non-uniform, causing a loss of geometric features. To facilitate the usability of point clouds in downstre…
CDT: Cascading Decision Trees for Explainable Reinforcement Learning
Zihan Ding, Pablo Hernandez-Leal, Gavin Weiguang Ding +2
Deep Reinforcement Learning (DRL) has recently achieved significant advances in various domains. However, explaining the policy of RL agents still remains an open problem due to se…
Some Insights into Lifelong Reinforcement Learning Systems
Changjian Li
A lifelong reinforcement learning system is a learning system that has the ability to learn through trail-and-error interaction with the environment over its lifetime. In this pape…
A Micro-Objective Perspective of Reinforcement Learning
Changjian Li, Krzysztof Czarnecki
The standard reinforcement learning (RL) formulation considers the expectation of the (discounted) cumulative reward. This is limiting in applications where we are concerned with n…