E-LIB Suche - Ergebnisse für: Archibald, Richard

1

Numerical Analysis for Convergence of a Sample-Wise Backpro..:

Archibald, Richard ; Bao, Feng ; Cao, Yanzhao.
SIAM Journal on Numerical Analysis. 62 (2024) 2 - p. 593-621 , 2024

Link: https://doi.org/10.1137/..

2

On the advantages of radial variation in assembly design fo..:

Sobes, Vladimir ; Popov, Emilian ; Archibald, Richard..
Nuclear Engineering and Design. 417 (2024) - p. 112820 , 2024

Link: https://doi.org/10.1016/..

3

A stochastic maximum principle approach for reinforcement l..:

Archibald, Richard ; Bao, Feng ; Yong, Jiongmin
Journal of Computational Physics. 488 (2023) - p. 112238 , 2023

Link: https://doi.org/10.1016/..

4

MGARD: A multigrid framework for high-performance, error-co..:

Gong, Qian ; Chen, Jieyang ; Whitney, Ben...
SoftwareX. 24 (2023) - p. 101590 , 2023

Link: https://doi.org/10.1016/..

5

Adaptive Generation of Training Data for ML Reduced Model C..:

, In: 2022 IEEE International Conference on Big Data (Big Data),

Cianciosa, Mark ; Archibald, Richard ; Elwasif, Wael... - p. 3408-3416 , 2022

Link: https://doi.org/10.1109/..

6

Kernel learning backward SDE filter for data assimilation:

Archibald, Richard ; Bao, Feng
Journal of Computational Physics. 455 (2022) - p. 111009 , 2022

Link: https://doi.org/10.1016/..

7

Strain-Induced asymmetry and on-site dynamics of silicon de..:

Dyck, Ondrej ; Bao, Feng ; Ziatdinov, Maxim...
Carbon Trends. 9 (2022) - p. 100189 , 2022

Link: https://doi.org/10.1016/..

8

Towards a Software Development Framework for Interconnected..:

, In: Communications in Computer and Information Science; Accelerating Science and Engineering Discoveries Through Integrated Research Infrastructure for Experiment, Big Data, Modeling and Simulation,

Thakur, Addi Malviya ; Hitefield, Seth ; McDonnell, Marshall... - p. 206-224 , 2022

Link: https://doi.org/10.1007/..

9

Artificial intelligence-driven thermal design for additivel..:

Popov, Emilian ; Archibald, Richard ; Hiscox, Briana.
Nuclear Engineering and Design. 395 (2022) - p. 111862 , 2022

Link: https://doi.org/10.1016/..

10

Maintaining Trust in Reduction: Preserving the Accuracy of ..:

, In: Driving Scientific and Engineering Discoveries Through the Integration of Experiment, Big Data, and Modeling and Simulation; Communications in Computer and Information Science,

Gong, Qian ; Liang, Xin ; Whitney, Ben... - p. 22-39 , 2022

Link: https://doi.org/10.1007/..

11

ARTIFICIAL INTELLIGENCE DESIGN OF NUCLEAR SYSTEMS EMPOWERED..:

Sobes, Vladimir ; Hiscox, Briana ; Popov, Emilian...
EPJ Web of Conferences. 247 (2021) - p. 06032 , 2021

Link: https://doi.org/10.1051/..

12

In situ compression artifact removal in scientific data usi..:

Madireddy, Sandeep ; Hwan Park, Ji ; Lee, Sunwoo...
Machine Learning: Science and Technology. 2 (2021) 2 - p. 025010 , 2021

Link: https://doi.org/10.1088/..

13

An Efficient Numerical Algorithm for Solving Data Driven Fe..:

Archibald, Richard ; Bao, Feng ; Yong, Jiongmin.
Journal of Scientific Computing. 85 (2020) 2 - p. , 2020

Link: https://doi.org/10.1007/..

14

Machine learning for neutron scattering at ORNL*:

Doucet, Mathieu ; Samarakoon, Anjana M ; Do, Changwoo...
Machine Learning: Science and Technology. 2 (2020) 2 - p. 023001 , 2020

Link: https://doi.org/10.1088/..

15

Super-resolution energy spectra from neutron direct-geometr..:

Islam, Fahima ; Lin, Jiao Y. Y. ; Archibald, Richard...
Review of Scientific Instruments. 90 (2019) 10 - p. , 2019

Link: https://doi.org/10.1063/..