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…
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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,…
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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…
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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.…
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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…
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In this paper, we propose SwarmNet -- a neural network architecture that can learn to predict and imitate the behavior of an observed swarm of…
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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…
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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…
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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…
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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…
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