| Counterfactual explanations for multivariate time series E Ates, B Aksar, VJ Leung, AK Coskun 2021 international conference on applied artificial intelligence (ICAPAI), 1-8, 2021 | 105 | 2021 |
| HPAS: An HPC performance anomaly suite for reproducing performance variations E Ates, Y Zhang, B Aksar, J Brandt, VJ Leung, M Egele, AK Coskun Proceedings of the 48th International Conference on Parallel Processing, 1-10, 2019 | 32 | 2019 |
| Proctor: A semi-supervised performance anomaly diagnosis framework for production hpc systems B Aksar, Y Zhang, E Ates, B Schwaller, O Aaziz, VJ Leung, J Brandt, ... High Performance Computing: 36th International Conference, ISC High …, 2021 | 21 | 2021 |
| From natural language to workflows: Towards emergent intelligence in robotic process automation T Chakraborti, Y Rizk, V Isahagian, B Aksar, F Fuggitti International Conference on Business Process Management, 123-137, 2022 | 17 | 2022 |
| E2EWatch: an end-to-end anomaly diagnosis framework for production HPC systems B Aksar, B Schwaller, O Aaziz, VJ Leung, J Brandt, M Egele, AK Coskun Euro-Par 2021: Parallel Processing: 27th International Conference on …, 2021 | 15 | 2021 |
| Prodigy: Towards unsupervised anomaly detection in production hpc systems B Aksar, E Sencan, B Schwaller, O Aaziz, VJ Leung, J Brandt, B Kulis, ... Proceedings of the International Conference for High Performance Computing …, 2023 | 9 | 2023 |
| Albadross: Active learning based anomaly diagnosis for production hpc systems B Aksar, E Sencan, B Schwaller, O Aaziz, VJ Leung, J Brandt, B Kulis, ... 2022 IEEE International Conference on Cluster Computing (CLUSTER), 369-380, 2022 | 7 | 2022 |
| Using monitoring data to improve hpc performance via network-data-driven allocation Y Zhang, B Aksar, O Aaziz, B Schwaller, J Brandt, V Leung, M Egele, ... 2021 IEEE High Performance Extreme Computing Conference (HPEC), 1-7, 2021 | 6 | 2021 |
| Runtime Performance Anomaly Diagnosis in Production HPC Systems Using Active Learning B Aksar, E Sencan, B Schwaller, O Aaziz, VJ Leung, J Brandt, B Kulis, ... IEEE Transactions on Parallel and Distributed Systems, 2024 | 3 | 2024 |
| Explainable Machine Learning Frameworks for Managing HPC Systems. E Ates, B Aksar, VJ Leung, AK Coskun Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2020 | 3 | 2020 |
| Towards Practical Machine Learning Frameworks for Performance Diagnostics in Supercomputers B Aksar, E Sencan, B Schwaller, VJ Leung, J Brandt, B Kulis, M Egele, ... Proceedings of the First Workshop on AI for Systems, 1-6, 2023 | 1 | 2023 |
| Comte: counterfactual explanations for supervised machine learning frameworks on multivariate time series data VJ Leung, E Ates, B Aksar, AK Coskun Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2021 | 1 | 2021 |
| A Machine Learning Approach to Understanding HPC Application Performance Variation. B Schwaller, B Aksar, OR Aaziz, E Ates, JM Brandt, A Coskun, M Egele, ... Sandia National Lab.(SNL-NM), Albuquerque, NM (United States); Sandia …, 2019 | 1 | 2019 |
| AD for Machine Learning Approach to Understanding HPC Application Performance Variation Poster. B Aksar, B Schwaller, OR Aaziz, E Ates, JM Brandt, A Coskun, M Egele, ... Sandia National Lab.(SNL-NM), Albuquerque, NM (United States); Sandia …, 2019 | 1 | 2019 |
| Multi-agent chatbot with multi-intent recognition B Aksar, Y Rizk, T Chakraborti US Patent 11,985,097, 2024 | | 2024 |
| Machine learning-based performance analytics for high-performance computing systems B Aksar Boston University, 2024 | | 2024 |
| Explaining natural-language-to-flow pipelines T Chakraborti, A Chaudhary, M Brachman, Q Pan, J Johnson, Y Rizk, ... US Patent App. 17/804,627, 2023 | | 2023 |
| TESS: A Multi-intent Parser for Conversational Multi-Agent Systems with Decentralized Natural Language Understanding Models B Aksar, Y Rizk, T Chakraborti arXiv preprint arXiv:2312.11828, 2023 | | 2023 |
| CoMTE: Counterfactual Explanations for Multivariate Time Series. E Ates, B Aksar, AK Coskun, VJ Leung Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2021 | | 2021 |
| Explainable Machine Learning Frameworks for Managing HPC Systems B Aksar, E Ates, VJ Leung, AK Coskun Workshop on Machine Learning for Computing Systems, Supercomputing'20, 2020 | | 2020 |
Ayse K CoskunProfessor in ECE Department, Boston UniversityBestätigte E-Mail-Adresse bei bu.edu