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ORCIDRick Archibald
Person information
- affiliation: Oak Ridge National Laboratory, TN, USA
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Journal Articles
- 2024
[j30]Rick Archibald
, Ben Whitney:
Haar-Like Wavelets on Hierarchical Trees. J. Sci. Comput. 99(1): 3 (2024)- [j29]Richard Archibald, Feng Bao, Yanzhao Cao, Hui Sun:
Numerical Analysis for Convergence of a Sample-Wise Backpropagation Method for Training Stochastic Neural Networks. SIAM J. Numer. Anal. 62(2): 593-621 (2024) - 2023
- [j28]Richard Archibald, Feng Bao, Jiongmin Yong:
A stochastic maximum principle approach for reinforcement learning with parameterized environment. J. Comput. Phys. 488: 112238 (2023) - [j27]Qian Gong, Jieyang Chen, Ben Whitney, Xin Liang, Viktor Reshniak, Tania Banerjee, Jaemoon Lee, Anand Rangarajan, Lipeng Wan, Nicolas Vidal, Qing Liu, Ana Gainaru, Norbert Podhorszki, Richard Archibald, Sanjay Ranka, Scott Klasky:
MGARD: A multigrid framework for high-performance, error-controlled data compression and refactoring. SoftwareX 24: 101590 (2023) - 2022
- [j26]Richard Archibald, Feng Bao:
Kernel learning backward SDE filter for data assimilation. J. Comput. Phys. 455: 111009 (2022) - 2021
- [j25]Mathieu Doucet, Anjana M. Samarakoon, Changwoo Do, William T. Heller, Richard Archibald, D. Alan Tennant, Thomas Proffen, Garrett E. Granroth:
Machine learning for neutron scattering at ORNL. Mach. Learn. Sci. Technol. 2(2): 23001 (2021) - [j24]Sandeep Madireddy, Ji Hwan Park, Sunwoo Lee, Prasanna Balaprakash, Shinjae Yoo, Wei-keng Liao, Cory D. Hauck, M. Paul Laiu, Richard Archibald:
In situ compression artifact removal in scientific data using deep transfer learning and experience replay. Mach. Learn. Sci. Technol. 2(2): 25010 (2021) - [j23]Mathieu Doucet, Richard K. Archibald, William T. Heller:
Machine learning for neutron reflectometry data analysis of two-layer thin films. Mach. Learn. Sci. Technol. 2(3): 35001 (2021) - [j22]William T. Heller, Mathieu Doucet, Richard K. Archibald:
Sas-temper: Software for fitting small-angle scattering data that provides automated reproducibility characterization. SoftwareX 16: 100849 (2021) - 2020
- [j21]Richard Archibald, Feng Bao, Jiongmin Yong, Tao Zhou:
An Efficient Numerical Algorithm for Solving Data Driven Feedback Control Problems. J. Sci. Comput. 85(2): 51 (2020) - 2019
- [j20]Katherine J. Evans, Richard K. Archibald, David J. Gardner, Matthew R. Norman, Mark A. Taylor, Carol S. Woodward, Patrick H. Worley:
Performance analysis of fully explicit and fully implicit solvers within a spectral element shallow-water atmosphere model. Int. J. High Perform. Comput. Appl. 33(2) (2019) - [j19]Richard Archibald, Feng Bao, Xuemin Tu:
A direct filter method for parameter estimation. J. Comput. Phys. 398 (2019) - 2016
- [j18]Feng Bao, Rick Archibald, Dipanshu Bansal, Olivier Delaire:
Hierarchical optimization for neutron scattering problems. J. Comput. Phys. 315: 39-51 (2016) - [j17]Rick Archibald, Anne Gelb, Rodrigo B. Platte:
Image Reconstruction from Undersampled Fourier Data Using the Polynomial Annihilation Transform. J. Sci. Comput. 67(2): 432-452 (2016) - 2015
- [j16]Wayne Joubert, Rick Archibald, Mark A. Berrill, W. Michael Brown, Markus Eisenbach, Ray W. Grout, Jeff Larkin, John M. Levesque, Bronson Messer, Matthew R. Norman, Bobby Philip, Ramanan Sankaran, Arnold N. Tharrington, John A. Turner:
Accelerated application development: The ORNL Titan experience. Comput. Electr. Eng. 46: 123-138 (2015) - [j15]Gabriel Wasserman, Rick Archibald, Anne Gelb:
Image Reconstruction from Fourier Data Using Sparsity of Edges. J. Sci. Comput. 65(2): 533-552 (2015) - 2014
- [j14]Rick Archibald, Clayton G. Webster:
Foreword. Int. J. Comput. Math. 91(4): 705-706 (2014) - [j13]Vishwas Rao, Rick Archibald, Katherine J. Evans:
Emulation to simulate low-resolution atmospheric data. Int. J. Comput. Math. 91(4): 770-780 (2014) - [j12]Rick Archibald, M. Chakoumakos, Tony Zhuang:
Characterizing the elements of Earth's radiative budget: Applying uncertainty quantification to the CESM. J. Comput. Sci. 5(2): 85-89 (2014) - 2013
- [j11]Ilene Carpenter, Rick Archibald, Katherine J. Evans, Jeffrey M. Larkin, Paulius Micikevicius, Matthew R. Norman, James Rosinski, Jim Schwarzmeier, Mark A. Taylor:
Progress towards accelerating HOMME on hybrid multi-core systems. Int. J. High Perform. Comput. Appl. 27(3): 335-347 (2013) - 2011
- [j10]John D. Jakeman, Richard Archibald, Dongbin Xiu:
Characterization of discontinuities in high-dimensional stochastic problems on adaptive sparse grids. J. Comput. Phys. 230(10): 3977-3997 (2011) - 2009
- [j9]Rick Archibald, Anne Gelb, Rishu Saxena, Dongbin Xiu:
Discontinuity detection in multivariate space for stochastic simulations. J. Comput. Phys. 228(7): 2676-2689 (2009) - [j8]Anthony M. Filippi, Rick Archibald:
Support Vector Machine-Based Endmember Extraction. IEEE Trans. Geosci. Remote. Sens. 47(3): 771-791 (2009) - 2007
- [j7]Rick Archibald, George Fann:
Feature Selection and Classification of Hyperspectral Images With Support Vector Machines. IEEE Geosci. Remote. Sens. Lett. 4(4): 674-677 (2007) - 2006
- [j6]Rick Archibald, Anne Gelb, Sigal Gottlieb, Jennifer K. Ryan:
One-sided Post-processing for the Discontinuous Galerkin Method Using ENO Type Stencil Choosing and the Local Edge Detection Method. J. Sci. Comput. 28(2-3): 167-190 (2006) - 2005
- [j5]Rick Archibald, Anne Gelb, Jungho Yoon:
Polynomial Fitting for Edge Detection in Irregularly Sampled Signals and Images. SIAM J. Numer. Anal. 43(1): 259-279 (2005) - 2004
- [j4]Rick Archibald, Jiuxiang Hu, Anne Gelb, Gerald E. Farin:
Improving the accuracy of volumetric segmentation using pre-processing boundary detection and image reconstruction. IEEE Trans. Image Process. 13(4): 459-466 (2004) - 2003
- [j3]Rick Archibald, Kewei Chen, Anne Gelb, Rosemary A. Renaut:
Improving tissue segmentation of human brain MRI through preprocessing by the Gegenbauer reconstruction method. NeuroImage 20(1): 489-502 (2003) - 2002
- [j2]Rick Archibald, Anne Gelb:
Reducing the Effects of Noise in Image Reconstruction. J. Sci. Comput. 17(1-4): 167-180 (2002) - [j1]Rick Archibald, Anne Gelb:
A method to reduce the Gibbs ringing artifact in MRI scans while keeping tissue boundary integrity. IEEE Trans. Medical Imaging 21(4): 305-319 (2002)
Conference and Workshop Papers
- 2022
- [c16]Rick Archibald, Mark R. Cianciosa, Cornwall Lau:
Improving Predictions Under Uncertainty of Material Plasma Device Operations. IEEE Big Data 2022: 3402-3407 - [c15]Mark R. Cianciosa, Richard Archibald, Wael R. Elwasif, Ana Gainaru, Jin Myung Park, Ross Whitfield:
Adaptive Generation of Training Data for ML Reduced Model Creation. IEEE Big Data 2022: 3408-3416 - [c14]Addi Malviya-Thakur, Seth Hitefield, Marshall T. McDonnell, Matthew Wolf, Richard Archibald, Lance Drane, Kevin Roccapriore, Maxim A. Ziatdinov, Jesse McGaha, Robert Smith, John Hetrick, Mark Abraham, Sergey Yakubov, Gregory R. Watson, Ben Chance, Clara Nguyen, Matthew Baker, J. Robert Michael, Elke Arenholz, Ben Mintz:
Towards a Software Development Framework for Interconnected Science Ecosystems. SMC 2022: 206-224 - 2021
- [c13]Xin Liang, Qian Gong, Jieyang Chen, Ben Whitney, Lipeng Wan, Qing Liu, David Pugmire, Rick Archibald, Norbert Podhorszki, Scott Klasky:
Error-controlled, progressive, and adaptable retrieval of scientific data with multilevel decomposition. SC 2021: 88 - [c12]Qian Gong, Xin Liang, Ben Whitney, Jong Youl Choi, Jieyang Chen, Lipeng Wan, Stéphane Ethier, Seung-Hoe Ku, Randy Michael Churchill, Choong-Seock Chang, Mark Ainsworth, Ozan Tugluk, Todd S. Munson, David Pugmire, Richard Archibald, Scott Klasky:
Maintaining Trust in Reduction: Preserving the Accuracy of Quantities of Interest for Lossy Compression. SMC 2021: 22-39 - 2020
- [c11]Rick Archibald, Edmond Chow, Eduardo F. D'Azevedo, Jack J. Dongarra, Markus Eisenbach, Rocco Febbo, Florent Lopez, Daniel Nichols, Stanimire Tomov, Kwai Wong, Junqi Yin:
Integrating Deep Learning in Domain Sciences at Exascale. SMC 2020: 35-50 - 2019
- [c10]Sunwoo Lee, Qiao Kang, Sandeep Madireddy, Prasanna Balaprakash, Ankit Agrawal, Alok N. Choudhary, Richard Archibald, Wei-keng Liao:
Improving Scalability of Parallel CNN Training by Adjusting Mini-Batch Size at Run-Time. IEEE BigData 2019: 830-839 - [c9]Brendan Sullivan, Rick Archibald, Venu Vandavasi, Patricia Langan, Leighton Coates, Vickie Lynch:
Volumetric Segmentation via Neural Networks Improves Neutron Crystallography Data Analysis. CCGRID 2019: 549-555 - 2017
- [c8]S. V. Venkatakrishnan, Ercan Cakmak, Hassina Z. Bilheux, Philip R. Bingham, Richard K. Archibald:
Model-based iterative reconstruction for neutron laminography. ACSSC 2017: 1864-1869 - 2016
- [c7]Eric J. Lingerfelt, Alex Belianinov, Eirik Endeve, O. Ovchinnikov, Suhas Somnath, Jose M. Borreguero, N. Grodowitz, B. Park, Richard K. Archibald, Christopher T. Symons, Sergei V. Kalinin, O. E. Bronson Messer, Mallikarjun Shankar, Stephen Jesse:
BEAM: A Computational Workflow System for Managing and Modeling Material Characterization Data in HPC Environments. ICCS 2016: 2276-2280 - 2015
- [c6]Rick Archibald, Katherine J. Evans, Andrew G. Salinger:
Accelerating Time Integration for the Shallow Water Equations on the Sphere Using GPUs. ICCS 2015: 2046-2055 - 2014
- [c5]Roisin Langan, Richard Archibald, Matthew Plumlee, Salil Mahajan, Daniel M. Ricciuto, Chengen Yang, Rui Mei, Jiafu Mao, Xiaoying Shi, Joshua S. Fu:
Stochastic Parameterization to Represent Variability and Extremes in Climate Modeling. ICCS 2014: 1146-1155 - 2012
- [c4]Rick Archibald, M. Chakoumakos, Tony Zhuang:
Characterizing the elements of Earth's radiative budget: Applying uncertainty quantification to the CESM. ICCS 2012: 1014-1020 - 2009
- [c3]Rick Archibald, Katherine J. Evans, J. B. Drake, James B. White III:
Time Acceleration Methods for Advection on the Cubed Sphere. ICCS (2) 2009: 253-262 - 2002
- [c2]Rick Archibald, Anne Gelb:
Reducing the effects of noise in MRI reconstruction. ISBI 2002: 497-500 - [c1]Anne Gelb, Rick Archibald:
Reducing the Gibbs ringing artifact in MRI scans while maintaining tissue boundary integrity. ISBI 2002: 923-926
Informal and Other Publications
- 2024
- [i7]Qian Gong, Jieyang Chen, Ben Whitney, Xin Liang, Viktor Reshniak, Tania Banerjee, Jaemoon Lee, Anand Rangarajan, Lipeng Wan, Nicolas Vidal, Qing Liu, Ana Gainaru, Norbert Podhorszki, Richard Archibald, Sanjay Ranka, Scott Klasky:
MGARD: A multigrid framework for high-performance, error-controlled data compression and refactoring. CoRR abs/2401.05994 (2024) - 2023
- [i6]Benjamin P. Russo, M. Paul Laiu, Richard Archibald:
Streaming Compression of Scientific Data via weak-SINDy. CoRR abs/2308.14962 (2023) - 2022
- [i5]Richard Archibald, Feng Bao:
A Kernel Learning Method for Backward SDE Filter. CoRR abs/2201.10600 (2022) - [i4]Zezhong Zhang, Richard Archibald, Feng Bao:
A PDE-based Adaptive Kernel Method for Solving Optimal Filtering Problems. CoRR abs/2203.05031 (2022) - [i3]Richard Archibald, Feng Bao, Yanzhao Cao, Hui Sun:
Convergence Analysis for Training Stochastic Neural Networks via Stochastic Gradient Descent. CoRR abs/2212.08924 (2022) - 2020
- [i2]Rick Archibald, Edmond Chow, Eduardo F. D'Azevedo, Jack J. Dongarra, Markus Eisenbach, Rocco Febbo, Florent Lopez, Daniel Nichols, Stanimire Tomov, Kwai Wong, Junqi Yin:
Integrating Deep Learning in Domain Sciences at Exascale. CoRR abs/2011.11188 (2020) - [i1]Richard Archibald, Feng Bao, Yanzhao Cao, He Zhang:
Uncertainty Quantification in Deep Learning through Stochastic Maximum Principle. CoRR abs/2011.14145 (2020)
Coauthor Index
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last updated on 2024-05-08 03:56 CEST by the dblp team
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