Publications
2024
P.-T. Bremer, G. Tourassi, W. Bethel, K. Gaither, V. Pascucci, and W. Xu. Report for the ASCR Workshop on Visualization for Scientific Discovery, Decision-Making, and Communication. United States: N. p., doi:10.2172/1845709. paper
X. Luo, W. Xu, B. T. Nadiga, Y. Ren, and S. Yoo, "Continuous Field Reconstruction from Sparse Observations with Implicit Neural Networks," The Twelfth International Conference on Learning Representations (ICLR), Vienna, Austria, May 2024. paper | webpage | code
W. Xu, D. F. DeSantis, X. Luo, A. Parmar, K. Tan, B. T. Nadiga, Y. Ren, and S. Yoo, "Studying the Impact of Latent Representations in Implicit Neural Networks for Scientific Continuous Field Reconstruction," AAAI co-held XAI4Sci workshop, Vancouver, Canada, Feb. 2024. paper
2023
M. Lin, Q. Guan, and W. Xu, "The Need for Better Evaluation of Realistic Quantum Processor Performance," ASCR Basic Research Needs in Quantum Computing and Networking workshop, position paper, July 2023. paper
A. Kumar, X. Zhang, H. Xin, H. Yan, X. Huang, W. Xu, and K. Mueller, "RadVolViz: An Information Display-Inspired Transfer Function Editor for Multivariate Volume Visualization," TVCG; presented in IEEE VIS 2023. paper
S. Ruan, R. Yuan, Y. Wang, Y. Lin, Y. Mao, W. Jiang, Z. Wang, W. Xu, and Q. Guan, "VENUS: A Geometrical Representation for Quantum State Visualization," EuroVis 2023. paper
2022
X. Luo, W. Xu, Y. Ren, S. Yoo, B. T. Nadiga, and A. Kareem, "Zero or Infinite Data? Knowledge Synchronized Machine Learning Emulation," NeurIPS co-held AI4Science workshop, Nov. 2022. paper
X. Luo, B. T. Nadiga, J. H. Park, Y. Ren, W. Xu, and S. Yoo, "A Bayesian Deep Learning Approach to Near-Term Climate Prediction, " Journal of Advances in Modeling Earth Systems (JAMES), Sept 2022. paper
A. Guite, T. Z. Islam, C. Kelly, and W. Xu, "Interactive Visual Analysis Tool for Anomaly Provenance Data," SC'22 poster, Nov. 2022.
X. Luo, A. Kareem, Y. Ren, W. Xu, and S. Yoo, "A Deep Finite Difference Emulator for the Fast Simulation of Coupled Viscous Burgers’ Equation," preprint
P.-T. Bremer, G. Tourassi, W. Bethel, K. Gaither, V. Pascucci, and W. Xu, “Visualization for Scientific Discovery, Decision-Making, and Communication,” in Summary Report from the ASCR Workshop on Visualization for Scientific Discovery, Decision-Making, and Communication, United States, Jan. 2022. paper
Peer-Temo Bremer, Georgia Tourassi, Wes Bethel, Kelly Gaither, Valerio Pascucci, and Wei Xu. Position papers for the ASCR workshop on visualization for scientific discovery, decision-making, and communication. United States, January 2022. paper
2021
I. Foster, W. Xu, et al, "Online data analysis and reduction: An important Co-design motif for extreme-scale computers". The international journal of high performance computing applications, Volume: 35 issue: 6, page(s): 617-635, 2021. paper
W. Xu, X. Luo, Y. Ren, J. H. Park, S. Yoo and B. T. Nadiga, "Feature Importance in a Deep Learning Climate Emulator, " AIMOCC workshop co-held with ICLR, 2021. paper
X. Huang, S. Jamonnak, Y. Zhao, T. H. Wu, W. Xu, "A Visual Designer of Layer-wise Relevance Propagation Models," EuroVis 2021. paper | video
2020
C. Kelly, S. Ha, K. Huck, H. Van Dam, L. Pouchard, G. Matyasfalvi, L. Tang, N. D’Imperio, W. Xu (Corresponding), S. Yoo, and K. K. Van Dam, "Chimbuko: A Workflow-Level Scalable Performance Trace Analysis Tool," In Situ Infrastructures for Enabling Extreme-scale Analysis and Visualization, co-held workshop with Supercomputing Conference (ISAV/SC), Nov. 2020. (Best Paper Award) paper | video
H. Li, Y. Lin, K. Mueller, and W. Xu, "Interpreting Galaxy Deblender GAN from the Discriminator's Perspective," the International Symposium on Visual Computing (ISVC), Oct. 2020. paper | video
X. Huang, S. Jamonnak, Y. Zhao, B. Wang, M. Hoai, K. Yager, W. Xu, "Interactive Visual Study of Multiple Attributes Learning Model of X-Ray Scattering Images," IEEE SCIVIS/IEEE TVCG, 2020. paper | video
2019
W. Xu, S. Ha, W. Zhong, S. Cheng, H. Yan, K. Yager, X. Huang, K. Mueller, and Y. S. Chu, "Visual Analytics for Scientific Data in NSLS II," Handbook on Big Data and Machine Learning in the Physical Sciences, World Scientific, Nov. 2019.
Y.-L. L. Fang, S. Ha, X. Huang, H.Yan, Z. Dong, Y. S. Chu, S. I .Campbell, W. Xu, and M. Lin, "Accelerated Computing for X-ray Ptychography at NSLS-II," Handbook on Big Data and Machine Learning in the Physical Sciences, World Scientific, Nov. 2019.
X. Huang, S. Jamonnak, Y. Zhao, B. Wang, M. H. Nguyen, K. Yager and W. Xu, "Visual Understanding of Multiple Attributes Learning Model of X-Ray Scattering Images," ICCV co-held XAIC Workshop 2019, Korea. paper | video
S. Ha, Y. Lin, X. Huang, H. Yan, and W. Xu, "An End-to-end Deep Convolutional Neural Network for a Multi-scale Image Matching and Localization Problem", CVPR co-held Image Matching Workshop 2019, California. paper
C. Xie, J. Wang, G. Matyasfalvi, H. Van Dam, K. Mueller, S. Yoo and W. Xu, "Exploratory Visual Analysis of Anomalous Runtime Behavior in Streaming High Performance Computing Applications," ICCS 2019, Portugal. paper | video
2018
C. Xie, W. Xu, K. Mueller, "A Visual Analytics Framework for the Detection of Anomalous Call Stack Trees in High Performance Computing Applications," IEEE VAST/IEEE TVCG 2018. paper | video
W. Zhong, W. Xu, K. G. Yager, G. S. Doerk, J. Zhao, Y. Tian, S. Ha, C. Xie, Y. Zhong, K. Mueller, K. K. Van Dam, “MultiSciView: Multivariate Scientific X-ray Image Visual Exploration with Cross-Data Space Views,” Visual Informatics Journal/IEEE PacificVAST workshop co-held with IEEE PacificVIS conference, Kobe, Japan, Apr. 2018. paper | video
C. Xie, W. Zhong, W. Xu, K. Mueller, “Visual Analytics of Heterogeneous Data using Hypergraph Learning,” ACM Transactions on Intelligent Systems and Technology (TIST), Special Issue on Visual Analytics, 2018. paper | video
S. Cheng, W. Xu, K. Mueller, “ColorMapND: A Data-Driven Approach for Mapping Multivariate Data to Color,” IEEE Trans. on Visualization and Computer Graphics (TVCG), 2018. paper | video
P. Zhang, F. Wang, W. Xu, Y. Li, "Multi-channel Generative Adversarial Network for Parallel Magnetic Resonance Imaging Reconstruction in k-space," MICCAI 2018, Spain. paper
Z. Dong, M. Lin, W. Xu, et al, "High-Performance Multi-Mode Ptychography Reconstruction on Distributed GPUs ," IEEE NYSDS, 2018.
B. Sun, A. Frez, W. Xu, “Immersive Visual Analysis to Explore Mystery at Wildlife Preserve,” IEEE Virtual Reality Conference, Germany, 2018.
2017
S. Cheng, W. Xu, K. Mueller, “RadViz Deluxe: An attribute-aware display for multivariate data,” Journal of Processes 5(4) 75, 2017. paper
C. Xie, W. Xu, K. Huck, S. Shende, H. Van Dam, K. Kleese Van Dam and Klaus Mueller, “Performance Visualization for TAU Instrumented Scientific Workflows”, International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (IVAPP), 2017.
W. Zhong, C. Xie, Y. Zhong, Y. Wang, W. Xu, S. Cheng and K. Mueller, “Evolutionary Visual Analysis of Deep Neural Networks,” Int’l Conf. on Machine Learning (ICML) Workshop on Visualization for Deep Learning, Sydney, Australia, Aug. 2017. paper | video
I. Foster, M. Ainsworth, B. Allen, J. Bessac, F. Cappello, J. Choi, E. Constantinescu, P. Davis, S. Di, W. Di, H. Guo, S. Klasky, K. Kleese Van Dam, T. Kurc, Q. Liu, A. Malik, K. Mehta, K. Mueller, T. Munson, G. Ostouchov, M. Parashar, T. Peterka, L. Pouchard, D. Tao, O. Tugluk, S. Wild, M. Wolf, J. Wozniak, W. Xu, S. Yoo, “Computing just what you need: Online data analysis and reduction at extreme scales,” Int’l European Conference on Parallel Processing, Aug. 2017.
L. Pouchard, A. Malik, H. Van Dam, C. Xie, W. Xu, K. K. Van Dam, “Capturing provenance as a diagnostic tool for workflow performance evaluation and optimization,” IEEE New York Scientific Data Summit (NYSDS), New York, 2017.
L. Li, H. Yan, W. Xu, D. Yu, A. Heroux, W.-K. Lee, S. Campbell, Y. Chu, “PyXRF: Python-based X-ray fluorescence analysis package,” SPIE on Optics + Photonics, 103890U, San Diego, CA 2017.
B. Sun, R. Jessamy, S. Ha, W. Xu, “A Tableau Case Study on Visual Analysis to Explore Mystery at Wildlife Preserve,” IEEE Visualization Conference VAST Challenge, 2017.
2016
C. Xie, W. Zhong, J. Kong, W. Xu, K. Mueller and F. Wang, “IEVQ: An Iterative Example-based Visual Query for Pathology Database,” the 2nd Int’l workshop on Data Management and Analytics for Medicine and Healthcare (DMAH), New Delhi, India, 2016.
S. Cheng, K. Mueller, W. Xu “A Framework to Visualize Temporal Behavioral Relationships in Streaming Multivariate Data,” IEEE New York Scientific Data Summit (NYSDS), New York, 2016.
W. Xu, K. Mueller, “Mining Behavior Patterns in Streaming Multivariate Data,” STREAM 2016: Streaming Requirements, Experience, Applications and Middleware Workshop, Tysons, Virginia, March 2016.
S. Cheng, W. Xu, W. Zhong and K. Mueller, “A Data-Driven Approach for Mapping Multivariate Data to Color,” IEEE Visualization Conference, Baltimore, ML, 2016.
W. Xu and D. Feng , “Studying Performance of A Penalized Maximum Likelihood Method for PET Reconstruction on Nvidia GPU and Intel Xeon Phi Coprocessor,” 4th International Conference on Image Formation in X-Ray Computed Tomography (CT Meeting), Bamberg, Germany, July 2016.
2015
W. Xu, Z. Zheng, E. Papenhausen, S. Ha and K. Mueller, “Iterative Cone-Beam CT Reconstruction on GPUs: A Computational Perspective”, Book Chapter, Graphic Processing Unit-based High Performance Computing in Radiation Therapy (Chapter 4), CRC Press, 2015.
S. Yao, C. Chang, W. Xu, N. Zhou, Y. K. Chen-Wiegart, J. Wang, J. Wang and D. Yu, “NNLSF: a fast and informative fitting method for XANES chemical mapping analysis”, International Symposium on Biomedical Imaging (ISBI), Brooklyn, NY, 2015.
2014
C. Chang, W. Xu, Y. Chen-Wiegart, J. Wang and D. Yu, “Improving chemical mapping algorithm and visualization in full-field hard x-ray spectroscopic imaging”, SPIE on Visualization and Data Analysis, 90170S, San Francisco, CA, 2014.
C. Q. Wu, X. Lin, D. Yu, W. Xu, L. Li, “End-to-end Delay Minimization for Scientific Workflows in Clouds under Budget Constraint,” Transactions on Cloud Computing 2014.
2013
W. Xu, S. Ha, Z. Zheng and K. Mueller, “A Comparative Study of Neighborhood Filters for Artifact Reduction in Iterative Low-Dose CT”, 12th Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine (Fully3D), Lake Tahoe, CA, 2013.
W. Xu, S. Ha and K. Mueller, “Database-Assisted Low-Dose CT Image Restoration”, Medical Physics, 40(3), 031109, pp. 1-7, 2013.
C. Chang, W. Xu, H. Yan, L. Li, Y. Chu and D. Yu, “Accelerating Differential Phase Contrast Imaging on Multi-core CPUs”, The 10th International Conference and Expo on Emerging Technologies for a Smarter World (CEWIT), Melville, NY, 2013.
2012
W. Xu and K. Mueller, “Efficient Low-Dose CT Artifact Mitigation Using An Artifact-Matched Prior Scan”, Medical Physics, vol. 39 (8), pp. 4748-4760, 2012.
W. Xu, S. Ha and K. Mueller, “Database-Assisted Low-Dose CT Image Restoration”, The 2nd Int’l Conf. on Image Formation in X-Ray CT (CT Meeting), Salt Lake City, Utah, 2012.
2011
W. Xu and K. Mueller, “Using GPUs to Learn Effective Parameter Settings for GPU-Accelerated Iterative CT Reconstruction Algorithms”, Book Chapter, GPU Computing Gems Emerald Edition (Chapter 43), Morgan Kaufmann 2011.
X. Zhao, W. Zeng, X. Gu, A. Kaufman, W. Xu and K. Mueller, “Conformal Magnifier: A Focus+Context Technique with Local Shape Preservation”, IEEE Trans. on Visualization and Computer Graphics (TVCG), 2011
W. Xu and K. Mueller, “A Reference Image Database Approach for NLM Filter-Regularized CT Reconstruction”, Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine (Fully3D), pp.116-119, Potsdam, Germany 2011.
Z. Zheng, W. Xu and K. Mueller, “Performance Tuning for CUDA-Accelerated Neighborhood Denoising Filters”, High Performance Image Reconstruction Workshop (HPIR), pp.52-55, Potsdam, Germany 2011.
2010
Z. Zheng, W. Xu and K. Mueller, “VDVR: Verifiable Volume Visualization of Projection-Based Data”, IEEE Transactions on Visualization and Computer Graphics (TVCG) / Special Issue IEEE Visualization Conference), Salt Lake City, UT 2010.
W. Xu, F. Xu, M. Jones, B. Keszthelyi, J. Sedat, D. Agard and K. Mueller, “High-Performance Iterative Electron Tomography Reconstruction with Long-Object Compensation using Graphics Processing Units (GPUs)”, Journal of Structural Biology (JSB) 171(2): 142-153, 2010.
F. Xu, W. Xu, M. Jones, B. Keszthelyi, J. Sedat, D. Agard and K. Mueller, “On the Efficiency of Iterative Ordered Subset Reconstruction Algorithms for Acceleration on GPUs”, Computer Methods and Programs in Biomedicine (CMPB) 98(3): 261-270, 2010.
C. Rojo, W. Xu and K. Mueller, “Street Light View: Enriching Navigable Panoramic Street View Maps with Informative Illumination Thumbnails”, IEEE Visualization Conference, Salt Lake City, UT 2010.
W. Xu and K. Mueller, “Evaluating Popular Non-Linear Image Processing Filters for their Use in Regularized Iterative CT”, IEEE Medical Imaging Conference (MIC), Knoxville TN 2010.
W. Xu and K. Mueller, “Parameter space visualizer: an interactive parameter selection interface for iterative CT reconstruction algorithms”, SPIE on Medical Imaging, 7625:76251Q, San Diego, CA 2010.
2009
W. Xu and K. Mueller, “Learning Effective Parameter Settings for Iterative CT Reconstruction Algorithms”, Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine (Fully3D), pp.251-254, Beijing, China 2009.
W. Xu and K. Mueller, “A Performance-Driven Study of Regularization Methods for GPU-Accelerated Iterative CT”, High Performance Image Reconstruction (HPIR) Workshop, pp.20-23, Beijing, China 2009 (Best paper award).
W. Xu and K. Mueller, “Accelerating regularized iterative CT reconstruction on commodity graphics hardware (GPU)”, IEEE International Symposium on Biomedical Imaging (ISBI), pp.1287-1290, Boston, MA 2009.
2005
W. Xu and Y. Chen, “Algorithms of Texture Recovery in Image Based Modeling”, 12th National Conference on Image and Graphics (NCIG) 2005, Beijing, China 2005 (in Chinese).