306 citations · 501 across the 4 of their papers we have counts for
4 papers
Superposition of many models into one
Brian Cheung, Alex Terekhov, Yubei Chen +2
We present a method for storing multiple models within a single set of parameters. Models can coexist in superposition and still be retrieved individually. In experiments with neur…
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…
Pixels to Voxels: Modeling Visual Representation in the Human Brain
Pulkit Agrawal, Dustin Stansbury, Jitendra Malik +1
The human brain is adept at solving difficult high-level visual processing problems such as image interpretation and object recognition in natural scenes. Over the past few years n…
Analyzing the Performance of Multilayer Neural Networks for Object Recognition
Pulkit Agrawal, Ross Girshick, Jitendra Malik
In the last two years, convolutional neural networks (CNNs) have achieved an impressive suite of results on standard recognition datasets and tasks. CNN-based features seem poised…