14.1k citations · 34.6k across the 53 of their papers we have counts for
4 papers · 1 filter
DARCCC: Detecting Adversaries by Reconstruction from Class Conditional Capsules
Nicholas Frosst, Sara Sabour, Geoffrey Hinton
We present a simple technique that allows capsule models to detect adversarial images. In addition to being trained to classify images, the capsule model is trained to reconstruct…
Assessing the Scalability of Biologically-Motivated Deep Learning Algorithms and Architectures
Sergey Bartunov, Adam Santoro, Blake A. Richards +3
The backpropagation of error algorithm (BP) is impossible to implement in a real brain. The recent success of deep networks in machine learning and AI, however, has inspired propos…
Large scale distributed neural network training through online distillation
Rohan Anil, Gabriel Pereyra, Alexandre Passos +3
Techniques such as ensembling and distillation promise model quality improvements when paired with almost any base model. However, due to increased test-time cost (for ensembles) a…
Trustless Machine Learning Contracts; Evaluating and Exchanging Machine Learning Models on the Ethereum Blockchain
A. Besir Kurtulmus, Kenny Daniel
Using blockchain technology, it is possible to create contracts that offer a reward in exchange for a trained machine learning model for a particular data set. This would allow use…