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Toward Generalizable Models of I/O Throughput.

M. Isakov, E. Rosario, S. Madireddy, P. Balaprakash, P. Carns, R. Ross, and M. Kinsy. ROSS@SC, page 41-49. IEEE, (2020)

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Prasanna Rajagopalan

Hara Prasanna Misra

Debi Prasanna Ganguly

Krishna Prasanna Mukerji

Prasanna Venkatesh Rangadurai

Other publications of authors with the same name

Neuromorphic Acceleration for Approximate Bayesian Inference on Neural Networks via Permanent Dropout.N. Wycoff, P. Balaprakash, and F. Xia. ICONS, page 9:1-9:4. ACM, (2019)Graph Neural Network Architecture Search for Molecular Property Prediction.S. Jiang, and P. Balaprakash. IEEE BigData, page 1346-1353. IEEE, (2020)F-Race and Iterated F-Race: An Overview.M. Birattari, Z. Yuan, P. Balaprakash, and T. Stützle. Experimental Methods for the Analysis of Optimization Algorithms, Springer, (2010)A Taxonomy of Error Sources in HPC I/O Machine Learning Models.M. Isakov, M. Currier, E. Rosario, S. Madireddy, P. Balaprakash, P. Carns, R. Ross, G. Lockwood, and M. Kinsy. SC, page 16:1-16:14. IEEE, (2022)Automated Continual Learning of Defect Identification in Coherent Diffraction Imaging.O. Yildiz, H. Chan, K. Raghavan, W. Judge, M. Cherukara, P. Balaprakash, S. Sankaranarayanan, and T. Peterka. AI4S, page 1-6. IEEE, (2022)Streamlining Ocean Dynamics Modeling with Fourier Neural Operators: A Multiobjective Hyperparameter and Architecture Optimization Approach.Y. Sun, O. Sowunmi, R. Egele, S. Narayanan, L. Roekel, and P. Balaprakash. CoRR, (2024)The Unreasonable Effectiveness Of Early Discarding After One Epoch In Neural Network Hyperparameter Optimization.R. Egele, F. Mohr, T. Viering, and P. Balaprakash. CoRR, (2024)AI Competitions and Benchmarks: Dataset Development.R. Egele, J. Júnior, J. van Rijn, I. Guyon, X. Baró, A. Clapés, P. Balaprakash, S. Escalera, T. Moeslund, and J. Wan. CoRR, (2024)Modeling I/O Performance Variability Using Conditional Variational Autoencoders.S. Madireddy, P. Balaprakash, P. Carns, R. Latham, R. Ross, S. Snyder, and S. Wild. CLUSTER, page 109-113. IEEE Computer Society, (2018)Efficient Mapping Between Void Shapes and Stress Fields Using Deep Convolutional Neural Networks With Sparse Data.A. Bhaduri, N. Ramachandra, S. Ravi, L. Luan, P. Pandita, P. Balaprakash, M. Anitescu, C. Sun, and L. Wang. J. Comput. Inf. Sci. Eng., (April 2024)

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Disambiguation of "Balaprakash, Prasanna"

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Toward Generalizable Models of I/O Throughput.

Please choose a person to relate this publication to

Prasanna Rajagopalan

Hara Prasanna Misra

Debi Prasanna Ganguly

Krishna Prasanna Mukerji

Prasanna Venkatesh Rangadurai

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Balaprakash, Prasanna"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Toward Generalizable Models of I/O Throughput.

Please choose a person to relate this publication to

Prasanna Rajagopalan

Hara Prasanna Misra

Debi Prasanna Ganguly

Krishna Prasanna Mukerji

Prasanna Venkatesh Rangadurai

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
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Toward Generalizable Models of I/O Throughput.