272 citations · 3.4k across the 163 of their papers we have counts for
14 papers · 1 filter
Training Behavior of Sparse Neural Network Topologies
Simon Alford, Ryan Robinett, Lauren Milechin +1
Improvements in the performance of deep neural networks have often come through the design of larger and more complex networks. As a result, fast memory is a significant limiting f…
Uncertainty Propagation in Deep Neural Networks Using Extended Kalman Filtering
Jessica S. Titensky, Hayden Jananthan, Jeremy Kepner
Extended Kalman Filtering (EKF) can be used to propagate and quantify input uncertainty through a Deep Neural Network (DNN) assuming mild hypotheses on the input distribution. This…
Visually Representing the Landscape of Mathematical Structures
Katherine Gravel, Hayden Jananthan, Jeremy Kepner
The information technology explosion has dramatically increased the application of new mathematical ideas and has led to an increasing use of mathematics across a wide range of fie…
Neural Network Topologies for Sparse Training
Ryan A. Robinett, Jeremy Kepner
The sizes of deep neural networks (DNNs) are rapidly outgrowing the capacity of hardware to store and train them. Research over the past few decades has explored the prospect of sp…
Hyperscaling Internet Graph Analysis with D4M on the MIT SuperCloud
Vijay Gadepally, Jeremy Kepner, Lauren Milechin +14
Detecting anomalous behavior in network traffic is a major challenge due to the volume and velocity of network traffic. For example, a 10 Gigabit Ethernet connection can generate o…
Database Operations in D4M.jl
Lauren Milechin, Vijay Gadepally, Jeremy Kepner
Each step in the data analytics pipeline is important, including database ingest and query. The D4M-Accumulo database connector has allowed analysts to quickly and easily ingest to…