306 citations · 1.5k across the 54 of their papers we have counts for
3 papers · 1 filter
Learning to Perform Physics Experiments via Deep Reinforcement Learning
Misha Denil, Pulkit Agrawal, Tejas D Kulkarni +3
When encountering novel objects, humans are able to infer a wide range of physical properties such as mass, friction and deformability by interacting with them in a goal driven way…
What makes ImageNet good for transfer learning?
Minyoung Huh, Pulkit Agrawal, Alexei A. Efros
The tremendous success of ImageNet-trained deep features on a wide range of transfer tasks begs the question: what are the properties of the ImageNet dataset that are critical for…
Learning to Poke by Poking: Experiential Learning of Intuitive Physics
Pulkit Agrawal, Ashvin Nair, Pieter Abbeel +2
We investigate an experiential learning paradigm for acquiring an internal model of intuitive physics. Our model is evaluated on a real-world robotic manipulation task that require…