Julie Bessac - RankMe

29 papers A 1C 1Journal 20Unranked 7

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Streaming Operator Inference for Model Reduction of Large-Scale Dynamical Systems. CoRR Tomoki Koike, Prakash Mohan, Marc T. Henry de Frahan, Julie Bessac, Elizabeth Qian
2026	J	`jnl`	Uncovering Physical Drivers of Dark Matter Halo Structures with Auxiliary-Variable-Guided Generative Models. CoRR Arkaprabha Ganguli, Anirban Samaddar, Florian Kéruzoré, Nesar Ramachandra, Julie Bessac, Sandeep Madireddy, Emil M. Constantinescu
2025	J	`jnl`	Enhancing Interpretability in Generative Modeling: Statistically Disentangled Latent Spaces Guided by Generative Factors in Scientific Datasets. CoRR Arkaprabha Ganguli, Nesar Ramachandra, Julie Bessac, Emil M. Constantinescu
2025	J	`jnl`	Enhancing interpretability in generative modeling: statistically disentangled latent spaces guided by generative factors in scientific datasets. Mach. Learn. Arkaprabha Ganguli, Nesar Ramachandra, Julie Bessac, Emil M. Constantinescu
2025	J	`jnl`	Multi-modal Bayesian Neural Network Surrogates with Conjugate Last-Layer Estimation. CoRR Ian Taylor, Juliane Mueller, Julie Bessac
2025	J	`jnl`	Multidimensional Distributional Neural Network Output Demonstrated in Super-Resolution of Surface Wind Speed. CoRR Harrison J. Goldwyn, Mitchell Krock, Johann Rudi, Daniel Getter, Julie Bessac
2025	J	`jnl`	Navigating Uncertainty: Challenges in Visualizing Ensemble Data and Surrogate Models for Decision Systems. IEEE Computer Graphics and Applications Kristi Potter, Sam Molnar, J. D. Laurence-Chasen, Yuhan Duan, Julie Bessac, Han-Wei Shen
2025	J	`jnl`	Operator Inference Aware Quadratic Manifolds with Isotropic Reduced Coordinates for Nonintrusive Model Reduction. CoRR Paul Schwerdtner, Prakash Mohan, Julie Bessac, Marc T. Henry de Frahan, Benjamin Peherstorfer
2025	A	`conf`	Statistical Treatment of Variable MPI Latencies and MPI-Communication Hiding for Matrix-Free Finite Element Operators. ICS Max Heldman, Johann Rudi, Julie Bessac
2024	J	`jnl`	Online learning of quadratic manifolds from streaming data for nonlinear dimensionality reduction and nonlinear model reduction. CoRR Paul Schwerdtner, Prakash Mohan, Aleksandra Pachalieva, Julie Bessac, Daniel O'Malley, Benjamin Peherstorfer
2024	—	`conf`	Uncertainty Visualization Challenges in Decision Systems with Ensemble Data & Surrogate Models. UncertaintyVis@VIS Sam Molnar, J. D. Laurence-Chasen, Yuhan Duan, Julie Bessac, Kristi Potter
2023	C	`conf`	A Lightweight, Effective Compressibility Estimation Method for Error-bounded Lossy Compression. CLUSTER Arkaprabha Ganguli, Robert Underwood, Julie Bessac, David Krasowska, Jon C. Calhoun, Sheng Di, Franck Cappello
2023	J	`jnl`	Black-Box Statistical Prediction of Lossy Compression Ratios for Scientific Data. CoRR Robert Underwood, Julie Bessac, David Krasowska, Jon C. Calhoun, Sheng Di, Franck Cappello
2023	J	`jnl`	Black-box statistical prediction of lossy compression ratios for scientific data. Int. J. High Perform. Comput. Appl. Robert Underwood, Julie Bessac, David Krasowska, Jon C. Calhoun, Sheng Di, Franck Cappello
2023	J	`jnl`	Neural networks for parameter estimation in intractable models. Comput. Stat. Data Anal. Amanda Lenzi, Julie Bessac, Johann Rudi, Michael L. Stein
2022	J	`jnl`	Statistical treatment of convolutional neural network super-resolution of inland surface wind for subgrid-scale variability quantification. CoRR Daniel Getter, Julie Bessac, Johann Rudi, Yan Feng
2022	—	`conf`	Understanding the Effects of Modern Compressors on the Community Earth Science Model. DRBSD@SC Robert Underwood, Julie Bessac, Sheng Di, Franck Cappello
2021	—	`conf`	Exploring Lossy Compressibility through Statistical Correlations of Scientific Datasets. DRBSD@SC David Krasowska, Julie Bessac, Robert Underwood, Jon C. Calhoun, Sheng Di, Franck Cappello
2021	J	`jnl`	Online data analysis and reduction: An important Co-design motif for extreme-scale computers. Int. J. High Perform. Comput. Appl. 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
2021	—	`conf`	Parameter Estimation with Dense and Convolutional Neural Networks Applied to the FitzHugh-Nagumo ODE. MSML Johann Rudi, Julie Bessac, Amanda Lenzi
2021	J	`jnl`	Power grid frequency prediction using spatiotemporal modeling. Stat. Anal. Data Min. Amanda Lenzi, Julie Bessac, Mihai Anitescu
2021	J	`jnl`	SDRBench: Scientific Data Reduction Benchmark for Lossy Compressors. CoRR Kai Zhao, Sheng Di, Xin Liang, Sihuan Li, Dingwen Tao, Julie Bessac, Zizhong Chen, Franck Cappello
2020	—	`conf`	Image Segmentation for Dust Detection Using Semi-supervised Machine Learning. IEEE BigData Manzhu Yu, Julie Bessac, Ling Xu, Aryya Gangopadhyay, Yingxi Rona Shi, Jianwu Wang
2020	J	`jnl`	Parameter Estimation with Dense and Convolutional Neural Networks Applied to the FitzHugh-Nagumo ODE. CoRR Johann Rudi, Julie Bessac, Amanda Lenzi
2020	—	`conf`	SDRBench: Scientific Data Reduction Benchmark for Lossy Compressors. IEEE BigData Kai Zhao, Sheng Di, Xin Liang, Sihuan Li, Dingwen Tao, Julie Bessac, Zizhong Chen, Franck Cappello
2020	J	`jnl`	Statistical Treatment of Inverse Problems Constrained by Differential Equations-Based Models with Stochastic Terms. SIAM/ASA J. Uncertain. Quantification Emil M. Constantinescu, Noémi Petra, Julie Bessac, Cosmin G. Petra
2019	J	`jnl`	Global Sensitivity Analysis for Statistical Model Parameters. SIAM/ASA J. Uncertain. Quantification Joseph L. Hart, Julie Bessac, Emil M. Constantinescu
2018	J	`jnl`	Efficient computation of derivatives for solving optimization problems in R and Python using SWIG-generated interfaces to ADOL-C. Optim. Methods Softw. Kshitij Kulshreshtha, Sri Hari Krishna Narayanan, Julie Bessac, K. Macintyre
2017	—	`conf`	Computing Just What You Need: Online Data Analysis and Reduction at Extreme Scales. Euro-Par 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