| A Bayesian approach to selecting hyperelastic constitutive models of soft tissue S Madireddy, B Sista, K Vemaganti Computer Methods in Applied Mechanics and Engineering 291, 102-122, 2015 | 48 | 2015 |
| Time-series learning of latent-space dynamics for reduced-order model closure R Maulik, A Mohan, B Lusch, S Madireddy, P Balaprakash, D Livescu Physica D: Nonlinear Phenomena 405, 132368, 2020 | 35 | 2020 |
| Bayesian calibration of hyperelastic constitutive models of soft tissue S Madireddy, B Sista, K Vemaganti Journal of the Mechanical Behavior of Biomedical Materials, Accepted for …, 2016 | 28 | 2016 |
| Machine learning based parallel I/O predictive modeling: A case study on Lustre file systems S Madireddy, P Balaprakash, P Carns, R Latham, R Ross, S Snyder, ... International Conference on High Performance Computing, 184-204, 2018 | 14 | 2018 |
| Analysis and correlation of application I/O performance and system-wide I/O activity S Madireddy, P Balaprakash, P Carns, R Latham, R Ross, S Snyder, ... 2017 International Conference on Networking, Architecture, and Storage (NAS …, 2017 | 12 | 2017 |
| Modeling i/o performance variability using conditional variational autoencoders S Madireddy, P Balaprakash, P Carns, R Latham, R Ross, S Snyder, ... 2018 IEEE International Conference on Cluster Computing (CLUSTER), 109-113, 2018 | 7 | 2018 |
| Uncertainty quantification using the nearest neighbor Gaussian process H Shi, EL Kang, BA Konomi, K Vemaganti, S Madireddy New Advances in Statistics and Data Science, 89-107, 2017 | 3 | 2017 |
| HPC I/O throughput bottleneck analysis with explainable local models M Isakov, E Rosario, S Madireddy, P Balaprakash, P Carns, R Ross, ... 2020 SC20: International Conference for High Performance Computing …, 2020 | 2 | 2020 |
| A Modular Deep Learning Pipeline for Galaxy-Scale Strong Gravitational Lens Detection and Modeling S Madireddy, N Li, N Ramachandra, P Balaprakash, S Habib, J Butler, ... arXiv preprint arXiv:1911.03867, 2020 | 2 | 2020 |
| Phase Segmentation in Atom-Probe Tomography Using Deep Learning-Based Edge Detection S Madireddy, DW Chung, T Loeffler, SKRS Sankaranarayanan, ... Scientific reports 9 (1), 1-10, 2019 | 2 | 2019 |
| Improving Scalability of Parallel CNN Training by Adjusting Mini-Batch Size at Run-Time S Lee, Q Kang, S Madireddy, P Balaprakash, A Agrawal, A Choudhary, ... 2019 IEEE International Conference on Big Data (Big Data), 830-839, 2019 | 2 | 2019 |
| Using recurrent neural networks for nonlinear component computation in advection-dominated reduced-order models R Maulik, V Rao, S Madireddy, B Lusch, P Balaprakash arXiv preprint arXiv:1909.09144, 2019 | 2 | 2019 |
| Adaptive Learning for Concept Drift in Application Performance Modeling S Madireddy, P Balaprakash, P Carns, R Latham, GK Lockwood, R Ross, ... Proceedings of the 48th International Conference on Parallel Processing, 1-11, 2019 | 2 | 2019 |
| On the Inference of Viscoelastic Constants from Stress Relaxation Experiments K Vemaganti, S Madireddy, S Kedari Mechanics of Time-Dependent Materials, 2019 | 2 | 2019 |
| Gauge: An Interactive Data-Driven Visualization Tool for HPC Application I/O Performance Analysis E del Rosario, M Currier, M Isakov, S Madireddy, P Balaprakash, P Carns, ... | 1 | 2020 |
| Calibration of hyperelastic constitutive models: the role of boundary conditions, search algorithms, and experimental variability K Kenja, S Madireddy, K Vemaganti Biomechanics and Modeling in Mechanobiology, 1-18, 2020 | 1 | 2020 |
| In situ compression artifact removal in scientific data using deep transfer learning and experience replay S Madireddy, JH Park, S Lee, P Balaprakash, S Yoo, W Liao, CD Hauck, ... Machine Learning: Science and Technology 2 (2), 025010, 2020 | | 2020 |
| Toward Generalizable Models of I/O Throughput M Isakov, E del Rosario, S Madireddy, P Balaprakash, P Carns, RB Ross, ... 2020 IEEE/ACM International Workshop on Runtime and Operating Systems for …, 2020 | | 2020 |
| Domain adaptation techniques for improved cross-domain study of galaxy mergers A Ćiprijanović, D Kafkes, S Jenkin, K Downey, GN Perdue, S Madireddy, ... arXiv preprint arXiv:2011.03591, 2020 | | 2020 |
| Snowmass2021-Letter of Interest Scientific AI Approaches in Computational Cosmology S Habib, N Ramachandra, X Dong, S Madireddy | | 2020 |
Prasanna BalaprakashComputer Scientist, Argonne National LaboratoryZweryfikowany adres z mcs.anl.gov
