79 citations · 83 across the 4 of their papers we have counts for
4 papers
Physics-informed Machine Learning of Parameterized Fundamental Diagrams
James Koch, Thomas Maxner, Vinay Amatya +2
Fundamental diagrams describe the relationship between speed, flow, and density for some roadway (or set of roadway) configuration(s). These diagrams typically do not reflect, howe…
Scaling the training of particle classification on simulated MicroBooNE events to multiple GPUs
Alex Hagen, Eric Church, Jan Strube +2
Measurements in Liquid Argon Time Projection Chamber (LArTPC) neutrino detectors, such as the MicroBooNE detector at Fermilab, feature large, high fidelity event images. Deep learn…
GossipGraD: Scalable Deep Learning using Gossip Communication based Asynchronous Gradient Descent
Jeff Daily, Abhinav Vishnu, Charles Siegel +2
In this paper, we present GossipGraD - a gossip communication protocol based Stochastic Gradient Descent (SGD) algorithm for scaling Deep Learning (DL) algorithms on large-scale sy…
What does fault tolerant Deep Learning need from MPI?
Vinay Amatya, Abhinav Vishnu, Charles Siegel +1
Deep Learning (DL) algorithms have become the de facto Machine Learning (ML) algorithm for large scale data analysis. DL algorithms are computationally expensive - even distributed…