137 citations · 211 across the 6 of their papers we have counts for
6 papers
Learning non-Markovian Decision-Making from State-only Sequences
Aoyang Qin, Feng Gao, Qing Li +2
Conventional imitation learning assumes access to the actions of demonstrators, but these motor signals are often non-observable in naturalistic settings. Additionally, sequential…
Generalized Inverse Planning: Learning Lifted non-Markovian Utility for Generalizable Task Representation
Sirui Xie, Feng Gao, Song-Chun Zhu
In searching for a generalizable representation of temporally extended tasks, we spot two necessary constituents: the utility needs to be non-Markovian to transfer temporal relatio…
Dark, Beyond Deep: A Paradigm Shift to Cognitive AI with Humanlike Common Sense
Yixin Zhu, Tao Gao, Lifeng Fan +9
Recent progress in deep learning is essentially based on a "big data for small tasks" paradigm, under which massive amounts of data are used to train a classifier for a single narr…
Learning Perceptual Inference by Contrasting
Chi Zhang, Baoxiong Jia, Feng Gao +3
"Thinking in pictures," [1] i.e., spatial-temporal reasoning, effortless and instantaneous for humans, is believed to be a significant ability to perform logical induction and a cr…
VRGym: A Virtual Testbed for Physical and Interactive AI
Xu Xie, Hangxin Liu, Zhenliang Zhang +5
We propose VRGym, a virtual reality testbed for realistic human-robot interaction. Different from existing toolkits and virtual reality environments, the VRGym emphasizes on buildi…
RAVEN: A Dataset for Relational and Analogical Visual rEasoNing
Chi Zhang, Feng Gao, Baoxiong Jia +2
Dramatic progress has been witnessed in basic vision tasks involving low-level perception, such as object recognition, detection, and tracking. Unfortunately, there is still an eno…