151 citations · 158 across the 3 of their papers we have counts for
3 papers
cs.AI2023★ 2 cited
PushWorld: A benchmark for manipulation planning with tools and movable obstacles
Ken Kansky, Skanda Vaidyanath, Scott Swingle +3
While recent advances in artificial intelligence have achieved human-level performance in environments like Starcraft and Go, many physical reasoning tasks remain challenging for m…
cs.AI2017★ 151 cited
Schema Networks: Zero-shot Transfer with a Generative Causal Model of Intuitive Physics
Ken Kansky, Tom Silver, David A. Mély +7
The recent adaptation of deep neural network-based methods to reinforcement learning and planning domains has yielded remarkable progress on individual tasks. Nonetheless, progress…
cs.CV2016★ 5 cited
Generative Shape Models: Joint Text Recognition and Segmentation with Very Little Training Data
Xinghua Lou, Ken Kansky, Wolfgang Lehrach +4
We demonstrate that a generative model for object shapes can achieve state of the art results on challenging scene text recognition tasks, and with orders of magnitude fewer traini…