David Hysom

Publication Activity (10 Years)

Years Active: 1997-2021
Publications (10 Years): 6

Top Topics

Generative Model

Maximum Entropy Principle

Hierarchical Hidden Markov Models

Top Venues

IEEE Trans. Vis. Comput. Graph.

Int. J. High Perform. Comput. Appl.

Publications

Sam Ade Jacobs, Tim Moon, Kevin McLoughlin, Derek Jones, David Hysom, Dong H. Ahn, John C. Gyllenhaal, Pythagoras Watson, Felice C. Lightstone, Jonathan E. Allen, Ian Karlin, Brian Van Essen
Enabling rapid COVID-19 small molecule drug design through scalable deep learning of generative models. Int. J. High Perform. Comput. Appl. 35 (5) (2021)
Shusen Liu, Jim Gaffney, J. Luc Peterson, Peter B. Robinson, Harsh Bhatia, Valerio Pascucci, Brian K. Spears, Peer-Timo Bremer, Di Wang, Dan Maljovec, Rushil Anirudh, Jayaraman J. Thiagarajan, Sam Ade Jacobs, Brian C. Van Essen, David Hysom, Jae-Seung Yeom
Scalable Topological Data Analysis and Visualization for Evaluating Data-Driven Models in Scientific Applications. IEEE Trans. Vis. Comput. Graph. 26 (1) (2020)
Sam Ade Jacobs, Brian Van Essen, David Hysom, Jae-Seung Yeom, Tim Moon, Rushil Anirudh, Jayaraman J. Thiagarajan, Shusen Liu, Peer-Timo Bremer, Jim Gaffney, Tom Benson, Peter B. Robinson, J. Luc Peterson, Brian K. Spears
Parallelizing Training of Deep Generative Models on Massive Scientific Datasets. CoRR (2019)
J. Luc Peterson, Rushil Anirudh, Kevin Athey, Benjamin Bay, Peer-Timo Bremer, Vic Castillo, Francesco Di Natale, David Fox, Jim A. Gaffney, David Hysom, Sam Ade Jacobs, Bhavya Kailkhura, Joe Koning, Bogdan Kustowski, Steven H. Langer, Peter B. Robinson, Jessica Semler, Brian K. Spears, Jayaraman J. Thiagarajan, Brian Van Essen, Jae-Seung Yeom
Merlin: Enabling Machine Learning-Ready HPC Ensembles. CoRR (2019)
Sam Ade Jacobs, Jim Gaffney, Tom Benson, Peter B. Robinson, J. Luc Peterson, Brian K. Spears, Brian Van Essen, David Hysom, Jae-Seung Yeom, Tim Moon, Rushil Anirudh, Jayaraman J. Thiagarajan, Shusen Liu, Peer-Timo Bremer
Parallelizing Training of Deep Generative Models on Massive Scientific Datasets. CLUSTER (2019)
Shusen Liu, Di Wang, Dan Maljovec, Rushil Anirudh, Jayaraman J. Thiagarajan, Sam Ade Jacobs, Brian C. Van Essen, David Hysom, Jae-Seung Yeom, Jim Gaffney, J. Luc Peterson, Peter B. Robinson, Harsh Bhatia, Valerio Pascucci, Brian K. Spears, Peer-Timo Bremer
Scalable Topological Data Analysis and Visualization for Evaluating Data-Driven Models in Scientific Applications. CoRR (2019)
Veselin Stoyanov, Claire Cardie, Nathan Gilbert, Ellen Riloff, David Buttler, David Hysom
Coreference Resolution with Reconcile. ACL (2) (2010)
Brian T. N. Gunney, Andrew M. Wissink, David Hysom
Parallel clustering algorithms for structured AMR. J. Parallel Distributed Comput. 66 (11) (2006)
Christopher T. Symons, Nagiza F. Samatova, Ramya Krishnamurthy, Byung-Hoon Park, Tarik Umar, David Buttler, Terence Critchlow, David Hysom
Multi-Criterion Active Learning in Conditional Random Fields. ICTAI (2006)
Andrew M. Wissink, David Hysom, Richard D. Hornung
Enhancing scalability of parallel structured AMR calculations. ICS (2003)
David Hysom, Alex Pothen
A Scalable Parallel Algorithm for Incomplete Factor Preconditioning. SIAM J. Sci. Comput. 22 (6) (2001)
David Hysom, Alex Pothen
Parallel Computation of ILU(k) Preconditioners Without Serial Bottlenecks. PPSC (1999)
David Hysom, Alex Pothen
Efficient Parallel Computation of ILU(k) Preconditioners. SC (1999)
Shaharuddin Salleh, Albert Y. Zomaya, David Hysom
Mapping the Single-Row Routing Problem to a Hypercube. PDPTA (1997)