85 citations · 150 across the 9 of their papers we have counts for
10 papers
Report of the 2026 Workshop on Next-Generation Ecosystems for Scientific Computing: Harnessing Community, Software, and AI for Cross-Disciplinary Team Science
Lois Curfman McInnes, Dorian Arnold, Prasanna Balaprakash +45
Scientific computing is undergoing rapid transformation as advances in artificial intelligence, heterogeneous computing, automation, and data-intensive research reshape not only co…
DataVault: A Data Storage Infrastructure for the Einstein Toolkit
Yufeng Luo, Roland Haas, Qian Zhang +1
Data sharing is essential in the numerical simulations research. We introduce a data repository, DataVault, that is designed for data sharing, search and analysis. A comparative st…
Enabling real-time multi-messenger astrophysics discoveries with deep learning
E. A. Huerta, Gabrielle Allen, Igor Andreoni +57
Multi-messenger astrophysics is a fast-growing, interdisciplinary field that combines data, which vary in volume and speed of data processing, from many different instruments that…
Cyberinfrastructure Requirements to Enhance Multi-messenger Astrophysics
Philip Chang, Gabrielle Allen, Warren Anderson +39
The identification of the electromagnetic counterpart of the gravitational wave event, GW170817, and discovery of neutrinos and gamma-rays from TXS 0506+056 heralded the new era of…
Deep Learning for Multi-Messenger Astrophysics: A Gateway for Discovery in the Big Data Era
Gabrielle Allen, Igor Andreoni, Etienne Bachelet +45
This report provides an overview of recent work that harnesses the Big Data Revolution and Large Scale Computing to address grand computational challenges in Multi-Messenger Astrop…
Multi-Messenger Astrophysics: Harnessing the Data Revolution
Gabrielle Allen, Warren Anderson, Erik Blaufuss +27
The past year has witnessed discovery of the first identified counterparts to a gravitational wave transient (GW 170817A) and a very high-energy neutrino (IceCube-170922A). These s…
Real-time regression analysis with deep convolutional neural networks
E. A. Huerta, Daniel George, Zhizhen Zhao +1
We discuss the development of novel deep learning algorithms to enable real-time regression analysis for time series data. We showcase the application of this new method with a tim…
Report on the Third Workshop on Sustainable Software for Science: Practice and Experiences (WSSSPE3)
Daniel S. Katz, Sou-Cheng T. Choi, Kyle E. Niemeyer +18
This report records and discusses the Third Workshop on Sustainable Software for Science: Practice and Experiences (WSSSPE3). The report includes a description of the keynote prese…
Second Workshop on Sustainable Software for Science: Practice and Experiences (WSSSPE2): Submission, Peer-Review and Sorting Process, and Results
Daniel S. Katz, Gabrielle Allen, Neil Chue Hong +6
This technical report discusses the submission and peer-review process used by the Second Workshop on Sustainable Software for Science: Practice and Experiences (WSSSPE2) and the r…
First Workshop on Sustainable Software for Science: Practice and Experiences (WSSSPE): Submission and Peer-Review Process, and Results
Daniel S. Katz, Gabrielle Allen, Neil Chue Hong +2
This technical report discusses the submission and peer-review process used by the First Workshop on on Sustainable Software for Science: Practice and Experiences (WSSSPE) and the…