Specifying meaningful weight priors for variational inference in Bayesian deep neural network (DNN) is a challenging problem, particularly for scaling to larger models involving high…
Natural Language Processing is a complex and important field of AI. It’s what allows AI assistants to understand human voices, chatbots to understand typed text,…
Two key aspects of autonomous systems are perception and decision making. The first, perception, has benefited tremendously from advances in deep learning in areas such…
Imitation Learning, where an agent learns how to perform a task based on a demonstration by another, is a common form of learning in robotics.…
Neural networks have been called a “black box” because parts of their decision making are famously opaque as processing happens in hidden layers. In a…
In this paper, we propose SwarmNet -- a neural network architecture that can learn to predict and imitate the behavior of an observed swarm of…
We present a deep learning system for testing graphics units by detecting novel visual corruptions in videos. Unlike previous work in which manual tagging was…
Machine programming is the field of research concerned with automating the development and maintenance of software (and, as a byproduct, hardware). Using the nomenclature defined…
This demo presents a novel data visualization solution for exploring the results of time series anomaly detection systems. When anomalies are reported, there is a…
Query optimization is one of the most challenging problems in database systems. Despite the progress made over the past decades, query optimizers remain extremely complex…
