Elise Jennings

According to our database, Elise Jennings authored at least 9 papers between 2015 and 2022.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2022

A Kubernetes 'Bridge' operator between cloud and external resources.

Boris Lublinsky, Elise Jennings, Viktória Spisaková

CoRR, 2022

2021

Bayesian neural networks at scale: a performance analysis and pruning study.

Himanshu Sharma, Elise Jennings

J. Supercomput., 2021

2020

Deploying deep learning in OpenFOAM with TensorFlow.

Romit Maulik, Himanshu Sharma, Saumil Patel, Bethany Lusch, Elise Jennings

CoRR, 2020

2019

Enabling real-time multi-messenger astrophysics discoveries with deep learning.

Eliu A. Huerta, Gabrielle Allen, Igor Andreoni, Javier Mauricio Antelis, Etienne Bachelet, G. Bruce Berriman, Federica B. Bianco, Rahul Biswas, Matias Carrasco Kind, Kyle Chard, Minsik Cho, Philip S. Cowperthwaite, Zachariah B. Etienne, Maya Fishbach, Francisco Förster, Daniel George, Tom Gibbs, Matthew J. Graham, William Gropp, Robert A. Gruendl, Anushri Gupta, Roland Haas, Sarah Habib, Elise Jennings, Margaret W. G. Johnson, Erik Katsavounidis, Daniel S. Katz, Asad Khan, Volodymyr V. Kindratenko, William T. C. Kramer, Xin Liu, Ashish Mahabal, Zsuzsa Márka, Kenton McHenry, Jonah Miller, Claudia Moreno, Mark S. Neubauer, Steve Oberlin, Alexander R. Olivas, Donald Petravick, Adam Rebei, Shawn Rosofsky, Milton Ruiz, Aaron Saxton, Bernard F. Schutz, Alexander G. Schwing, Ed Seidel, Stuart L. Shapiro, Hongyu Shen, Yue Shen, Leo Singer, Brigitta M. Sipocz, Lunan Sun, John Towns, Antonios Tsokaros, Wei Wei, Jack Wells, Timothy J. Williams, Jinjun Xiong, Zhizhen Zhao

CoRR, 2019

Deep Learning for Multi-Messenger Astrophysics: A Gateway for Discovery in the Big Data Era.

Gabrielle Allen, Igor Andreoni, Etienne Bachelet, G. Bruce Berriman, Federica B. Bianco, Rahul Biswas, Matias Carrasco Kind, Kyle Chard, Minsik Cho, Philip S. Cowperthwaite, Zachariah B. Etienne, Daniel George, Tom Gibbs, Matthew J. Graham, William Gropp, Anushri Gupta, Roland Haas, Eliu A. Huerta, Elise Jennings, Daniel S. Katz, Asad Khan, Volodymyr V. Kindratenko, William T. C. Kramer, Xin Liu, Ashish Mahabal, Kenton McHenry, J. M. Miller, Mark S. Neubauer, Steve Oberlin, Alexander Reinefeld, Shawn Rosofsky, Milton Ruiz, Aaron Saxton, Bernard F. Schutz, Alexander G. Schwing, Ed Seidel, Stuart L. Shapiro, Hongyu Shen, Yue Shen, Brigitta Miksztai-Réthey, Lunan Sun, John Towns, Antonios Tsokaros, Wei Wei, Jack Wells, Timothy J. Williams, Jinjun Xiong, Zhizhen Zhao

CoRR, 2019

Scaling Distributed Training of Flood-Filling Networks on HPC Infrastructure for Brain Mapping.

Wushi Dong, Nicola J. Ferrier, Narayanan Kasthuri, Peter Littlewood, Murat Keçeli, Rafael Vescovi, Hanyu Li, Corey Adams, Elise Jennings, Samuel Flender, Thomas D. Uram, Venkatram Vishwanath

Proceedings of the Third IEEE/ACM Workshop on Deep Learning on Supercomputers, 2019

A Generalized Statistics-Based Model for Predicting Network-Induced Variability.

Sudheer Chunduri, Elise Jennings, Kevin Harms, Christopher Knight, Scott Parker

Proceedings of the 2019 IEEE/ACM Performance Modeling, 2019

2017

<i>astroABC</i> : An Approximate Bayesian Computation Sequential Monte Carlo sampler for cosmological parameter estimation.

Elise Jennings, Maeve Madigan

Astron. Comput., 2017

2015

CosmoSIS: Modular cosmological parameter estimation.

Joe Zuntz, Marc F. Paterno, Elise Jennings, Douglas H. Rudd, Alessandro Manzotti, Scott Dodelson, Sarah Bridle, Saba Sehrish, Jim Kowalkowski

Astron. Comput., 2015