| Deep Reinforcement Learning for Network Slicing with Heterogeneous Resource Requirements and Time Varying Traffic Dynamics J Koo, VB Mendiratta, MR Rahman, A Walid 15th International Conference on Network and Service Management, CNSM 2019 …, 2019 | 69 | 2019 |
| Application of machine learning and artificial intelligence to extend EFIT equilibrium reconstruction LL Lao, S Kruger, C Akçay, P Balaprakash, TA Bechtel, E Howell, J Koo, ... Plasma Physics and Controlled Fusion 64 (7), 074001, 2022 | 49 | 2022 |
| ytopt: Autotuning scientific applications for energy efficiency at large scales X Wu, P Balaprakash, M Kruse, J Koo, B Videau, P Hovland, V Taylor, ... Concurrency and Computation: Practice and Experience, e8322, 2024 | 20 | 2024 |
| Combined convolutional and recurrent neural networks for hierarchical classification of images J Koo, D Klabjan, J Utke 2020 IEEE International Conference on Big Data, Atlanta, GA, USA, 2020 | 18 | 2020 |
| Hpc storage service autotuning using variational-autoencoder-guided asynchronous bayesian optimization M Dorier, R Egele, P Balaprakash, J Koo, S Madireddy, S Ramesh, ... 2022 IEEE International Conference on Cluster Computing (CLUSTER), 381-393, 2022 | 13 | 2022 |
| Customized Monte Carlo Tree Search for LLVM/Polly's Composable Loop Optimization Transformations J Koo, P Balaprakash, M Kruse, X Wu, P Hovland, M Hall 12th IEEE International Workshop on Performance Modeling, Benchmarking and …, 2021 | 11 | 2021 |
| Improved Classification Based on Deep Belief Networks J Koo, D Klabjan 29th International Conference on Artificial Neural Networks, Bratislava …, 2020 | 9 | 2020 |
| A Unified Defect Pattern Analysis of Wafer Maps Using Density-Based Clustering J Koo, S Hwang IEEE Access 9, 78873-78882, 2021 | 8 | 2021 |
| Transfer-learning-based Autotuning using Gaussian Copula T Randall*, J Koo*, B Videau, M Kruse, X Wu, P Hovland, M Hall, R Ge, ... Proceedings of the 37th International Conference on Supercomputing, 37-49, 2023 | 3 | 2023 |
| An inverse classification framework with limited budget and maximum number of perturbed samples J Koo, D Klabjan, J Utke Expert Systems with Applications 212, 118761, 2023 | 3* | 2023 |
| Neuromorphic architectures for edge computing under extreme environments A Yanguas-Gil, J Koo, S Madireddy, P Balaprakash, JW Elam, AU Mane 2021 IEEE Space Computing Conference (SCC), 39-45, 2021 | 3 | 2021 |
| Analysis of defective patterns on wafers in semiconductor manufacturing: A bibliographical review BJ Yum, JH Koo, SJ Kim 2012 IEEE International Conference on Automation Science and Engineering …, 2012 | 3 | 2012 |
| EFIT-Prime: Probabilistic and physics-constrained reduced-order neural network model for equilibrium reconstruction in DIII-D S Madireddy, C Akçay, SE Kruger, TB Amara, X Sun, J McClenaghan, ... Physics of Plasmas 31 (9), 2024 | 2 | 2024 |
| Overview and progress of the EFIT-AI project S Kruger, L Lao, C Akcay, T Bechtel, Y Liu, J McClenaghan, D Orozco, ... APS Division of Plasma Physics Meeting Abstracts 2022, PP11. 057, 2022 | 1 | 2022 |
| An inverse classification framework with limited budget and maximum number of perturbed samples (vol 212, 118761, 2023) J Koo, D Klabjan, J Utke EXPERT SYSTEMS WITH APPLICATIONS 254, 2024 | | 2024 |
| Corrigendum to “An inverse classification framework with limited budget and maximum number of perturbed samples”(Expert Systems With Applications (2023) 212,(S0957417422017791 … J Koo, D Klabjan, J Utke Expert Systems with Applications 254, 124629, 2024 | | 2024 |
| Machine Learning Based Surrogate Models for Knock Prediction in Syngas (H₂/CO) Added SI Engine Combustion T Han, J Koo Journal of Energy & Climate Change 19 (1), 49-60, 2024 | | 2024 |
| Model order reduction of magnetic and MSE EFIT reconstructions with neural networks C Akcay, J Koo, S Madireddy, L Lao, X Sun, Y Liu, P Balaprakash APS Division of Plasma Physics Meeting Abstracts 2022, CO03. 007, 2022 | | 2022 |
| Model Order Reduction of the Plasma Equilibrium Reconstruction framework EFIT with Deep Neural Networks J Koo, S Madireddy, C Akcay, T Bechtel, S Kruger, Y Liu, X Sun, ... APS Division of Plasma Physics Meeting Abstracts 2022, GO05. 011, 2022 | | 2022 |
| A Mathematical View of the EFIT-AI Project S Kruger, E Howell, J Leddy, L Lao, C Akcay, T Bechtel, J McClenaghan, ... APS Division of Plasma Physics Meeting Abstracts 2021, GP11. 033, 2021 | | 2021 |
Prasanna BalaprakashDirector of AI Programs and Distinguished R&D Staff Scientist, Oak Ridge National Laboratoryכתובת אימייל מאומתת בדומיין ornl.gov