activity
20182020
most citedBenchmarking Model-Based Reinforcement Learning

239 citations · 435 across the 5 of their papers we have counts for

collaborators

6 papers

cs.GR202013 cited

UniCon: Universal Neural Controller For Physics-based Character Motion

Tingwu Wang, Yunrong Guo, Maria Shugrina +1

The field of physics-based animation is gaining importance due to the increasing demand for realism in video games and films, and has recently seen wide adoption of data-driven tec…

cs.CV202074 cited

Learning to Generate Diverse Dance Motions with Transformer

Jiaman Li, Yihang Yin, Hang Chu +4

With the ongoing pandemic, virtual concerts and live events using digitized performances of musicians are getting traction on massive multiplayer online worlds. However, well chore…

cs.LG2019239 cited

Benchmarking Model-Based Reinforcement Learning

Tingwu Wang, Xuchan Bao, Ignasi Clavera +7

Model-based reinforcement learning (MBRL) is widely seen as having the potential to be significantly more sample efficient than model-free RL. However, research in model-based RL h…

cs.LG201976 cited

Exploring Model-based Planning with Policy Networks

Tingwu Wang, Jimmy Ba

Model-based reinforcement learning (MBRL) with model-predictive control or online planning has shown great potential for locomotion control tasks in terms of both sample efficiency…

cs.LG201933 cited

Neural Graph Evolution: Towards Efficient Automatic Robot Design

Tingwu Wang, Yuhao Zhou, Sanja Fidler +1

Despite the recent successes in robotic locomotion control, the design of robot relies heavily on human engineering. Automatic robot design has been a long studied subject, but the…

cs.CV2018

VirtualHome: Simulating Household Activities via Programs

Xavier Puig, Kevin Ra, Marko Boben +4

In this paper, we are interested in modeling complex activities that occur in a typical household. We propose to use programs, i.e., sequences of atomic actions and interactions, a…