Artificial intelligence and deep learning applications for automotive manufacturing A Luckow, K Kennedy, M Ziolkowski, E Djerekarov, M Cook, E Duffy, ... 2018 IEEE International Conference on Big Data (Big Data), 3144-3152, 2018 | 57 | 2018 |
Beinit: Avoiding barren plateaus in variational quantum algorithms A Kulshrestha, I Safro 2022 IEEE international conference on quantum computing and engineering (QCE …, 2022 | 30 | 2022 |
Accelerating COVID-19 research with graph mining and transformer-based learning I Tyagin, A Kulshrestha, J Sybrandt, K Matta, M Shtutman, I Safro Proceedings of the AAAI Conference on Artificial Intelligence 36 (11), 12673 …, 2022 | 4 | 2022 |
CONFAIR: Configurable and Interpretable Algorithmic Fairness A Kulshrestha, I Safro arXiv preprint arXiv:2111.08878, 2021 | 2 | 2021 |
Learning to Optimize Quantum Neural Networks Without Gradients A Kulshrestha, X Liu, H Ushijima-Mwesigwa, I Safro 2023 IEEE International Conference on Quantum Computing and Engineering (QCE …, 2023 | 1 | 2023 |
A MACHINE LEARNING APPROACH TO IMPROVE SCALABILITY AND ROBUSTNESS OF VARIATIONAL QUANTUM CIRCUITS A Kulshrestha | | 2024 |
QArchSearch: A Scalable Quantum Architecture Search Package A Kulshrestha, I Safro, Y Alexeev Proceedings of the SC'23 Workshops of The International Conference on High …, 2023 | | 2023 |
QArchSearch: A Scalable Quantum Architecture Search Package IS Ankit Kulshrestha, Danylo Lykov, Yuri Alexeev Supercomputing 2023, 2023 | | 2023 |
Cobol2Vec: Learning Representations of Cobol code A Kulshrestha, V Lele arXiv preprint arXiv:2201.09448, 2022 | | 2022 |
Coping with Mistreatment in Fair Algorithms A Kulshrestha, I Safro arXiv preprint arXiv:2102.10750, 2021 | | 2021 |
Accelerating COVID-19 research with graph mining and transformer-based learning (preprint) I Tyagin, A Kulshrestha, J Sybrandt, K Matta, M Shtutman, I Safro | | 2021 |
Compressing Deep Neural Networks via Knowledge Distillation A Kulshrestha Clemson University, 2019 | | 2019 |