Given a visual scene, humans have strong intuitions about how a scene ca...
Effective planning of long-horizon deformable object manipulation requir...
Decentralized learning has been advocated and widely deployed to make
ef...
It is a long-standing problem to find effective representations for trai...
Modeling and manipulating elasto-plastic objects are essential capabilit...
Objects' motions in nature are governed by complex interactions and thei...
We consider the problem of sequential robotic manipulation of deformable...
We present a method to learn compositional predictive models from image
...
Tactile sensing is critical for humans to perform everyday tasks. While
...
Humans have a strong intuitive understanding of the 3D environment aroun...
Predictive models have been at the core of many robotic systems, from
qu...
Causal discovery is at the core of human cognition. It enables us to rea...
Convolutional Neural Networks (CNNs) have proved exceptional at learning...
Humans intuitively recognize objects' physical properties and predict th...
Finding an embedding space for a linear approximation of a nonlinear
dyn...
The ability to reason about temporal and causal events from videos lies ...
Humans perceive the world using multi-modal sensory inputs such as visio...
Real-life control tasks involve matter of various substances---rigid or ...
There has been an increasing interest in learning dynamics simulators fo...
The goal of imitation learning is to mimic expert behavior without acces...
Dense object detection and temporal tracking are needed across applicati...
This paper presents a method for face detection in the wild, which integ...