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ORCIDJulie Bessac
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2020 – today
- 2024
[c8]Sam Molnar, J. D. Laurence-Chasen, Yuhan Duan, Julie Bessac, Kristi Potter:
Uncertainty Visualization Challenges in Decision Systems with Ensemble Data & Surrogate Models. UncertaintyVis@VIS 2024: 12-16- [i5]Paul Schwerdtner, Prakash Mohan, Aleksandra Pachalieva, Julie Bessac, Daniel O'Malley, Benjamin Peherstorfer:
Online learning of quadratic manifolds from streaming data for nonlinear dimensionality reduction and nonlinear model reduction. CoRR abs/2409.02703 (2024) - 2023
- [j7]Amanda Lenzi
, Julie Bessac, Johann Rudi, Michael L. Stein:
Neural networks for parameter estimation in intractable models. Comput. Stat. Data Anal. 185: 107762 (2023) - [j6]Robert Underwood, Julie Bessac, David Krasowska, Jon C. Calhoun, Sheng Di, Franck Cappello:
Black-box statistical prediction of lossy compression ratios for scientific data. Int. J. High Perform. Comput. Appl. 37(3-4): 412-433 (2023) - [c7]Arkaprabha Ganguli, Robert Underwood, Julie Bessac, David Krasowska, Jon C. Calhoun, Sheng Di, Franck Cappello:
A Lightweight, Effective Compressibility Estimation Method for Error-bounded Lossy Compression. CLUSTER 2023: 247-258 - [i4]Robert Underwood, Julie Bessac, David Krasowska, Jon C. Calhoun, Sheng Di, Franck Cappello:
Black-Box Statistical Prediction of Lossy Compression Ratios for Scientific Data. CoRR abs/2305.08801 (2023) - 2022
- [c6]Robert Underwood, Julie Bessac, Sheng Di, Franck Cappello:
Understanding the Effects of Modern Compressors on the Community Earth Science Model. DRBSD@SC 2022: 1-10 - [i3]Daniel Getter, Julie Bessac, Johann Rudi, Yan Feng:
Statistical treatment of convolutional neural network super-resolution of inland surface wind for subgrid-scale variability quantification. CoRR abs/2211.16708 (2022) - 2021
- [j5]Ian T. Foster, Mark Ainsworth, Julie Bessac, Franck Cappello, Jong Choi, Sheng Di, Zichao Wendy Di, Ali Murat Gok, Hanqi Guo, Kevin A. Huck, Christopher Kelly, Scott Klasky, Kerstin Kleese van Dam, Xin Liang, Kshitij Mehta, Manish Parashar, Tom Peterka, Line Pouchard, Tong Shu, Ozan Tugluk, Hubertus Van Dam, Lipeng Wan, Matthew Wolf, Justin M. Wozniak, Wei Xu, Igor Yakushin, Shinjae Yoo, Todd S. Munson:
Online data analysis and reduction: An important Co-design motif for extreme-scale computers. Int. J. High Perform. Comput. Appl. 35(6): 617-635 (2021) - [j4]Amanda Lenzi, Julie Bessac, Mihai Anitescu:
Power grid frequency prediction using spatiotemporal modeling. Stat. Anal. Data Min. 14(6): 662-675 (2021) - [c5]Johann Rudi, Julie Bessac, Amanda Lenzi:
Parameter Estimation with Dense and Convolutional Neural Networks Applied to the FitzHugh-Nagumo ODE. MSML 2021: 781-808 - [c4]David Krasowska, Julie Bessac, Robert Underwood, Jon C. Calhoun, Sheng Di, Franck Cappello:
Exploring Lossy Compressibility through Statistical Correlations of Scientific Datasets. DRBSD@SC 2021: 47-53 - [i2]Kai Zhao, Sheng Di, Xin Liang, Sihuan Li, Dingwen Tao, Julie Bessac, Zizhong Chen, Franck Cappello:
SDRBench: Scientific Data Reduction Benchmark for Lossy Compressors. CoRR abs/2101.03201 (2021) - 2020
- [j3]Emil M. Constantinescu, Noémi Petra, Julie Bessac, Cosmin G. Petra:
Statistical Treatment of Inverse Problems Constrained by Differential Equations-Based Models with Stochastic Terms. SIAM/ASA J. Uncertain. Quantification 8(1): 170-197 (2020) - [c3]Manzhu Yu, Julie Bessac, Ling Xu, Aryya Gangopadhyay, Yingxi Rona Shi, Jianwu Wang:
Image Segmentation for Dust Detection Using Semi-supervised Machine Learning. IEEE BigData 2020: 1745-1754 - [c2]Kai Zhao, Sheng Di, Xin Liang, Sihuan Li, Dingwen Tao, Julie Bessac, Zizhong Chen, Franck Cappello:
SDRBench: Scientific Data Reduction Benchmark for Lossy Compressors. IEEE BigData 2020: 2716-2724 - [i1]Johann Rudi, Julie Bessac, Amanda Lenzi:
Parameter Estimation with Dense and Convolutional Neural Networks Applied to the FitzHugh-Nagumo ODE. CoRR abs/2012.06691 (2020)
2010 – 2019
- 2019
- [j2]Joseph L. Hart, Julie Bessac, Emil M. Constantinescu:
Global Sensitivity Analysis for Statistical Model Parameters. SIAM/ASA J. Uncertain. Quantification 7(1): 67-92 (2019) - 2018
- [j1]Kshitij Kulshreshtha, Sri Hari Krishna Narayanan, Julie Bessac, K. Macintyre:
Efficient computation of derivatives for solving optimization problems in R and Python using SWIG-generated interfaces to ADOL-C. Optim. Methods Softw. 33(4-6): 1173-1191 (2018) - 2017
- [c1]Ian T. Foster, Mark Ainsworth, Bryce Allen, Julie Bessac, Franck Cappello, Jong Youl Choi, Emil M. Constantinescu, Philip E. Davis, Sheng Di, Zichao Wendy Di, Hanqi Guo, Scott Klasky, Kerstin Kleese van Dam, Tahsin M. Kurç, Qing Liu, Abid Malik, Kshitij Mehta, Klaus Mueller, Todd S. Munson, George Ostrouchov, Manish Parashar, Tom Peterka, Line Pouchard, Dingwen Tao, Ozan Tugluk, Stefan M. Wild, Matthew Wolf, Justin M. Wozniak, Wei Xu, Shinjae Yoo:
Computing Just What You Need: Online Data Analysis and Reduction at Extreme Scales. Euro-Par 2017: 3-19
Coauthor Index
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