Ankit Kulshrestha

According to our database, Ankit Kulshrestha authored at least 13 papers between 2018 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2025

Neural Architecture Search Algorithms for Quantum Autoencoders.

Ankit Kulshrestha, Xiaoyuan Liu, Hayato Ushijima-Mwesigwa, Ilya Safro

CoRR, September, 2025

Partition-based Surface Code Compilation.

Hanjing Xu, Xiaoyuan Liu, Ankit Kulshrestha, Hayato Ushijima-Mwesigwa

Proceedings of the IEEE High Performance Extreme Computing Conference, 2025

2024

QAdaPrune: Adaptive Parameter Pruning For Training Variational Quantum Circuits.

Ankit Kulshrestha, Xiaoyuan Liu, Hayato Ushijima-Mwesigwa, Bao Bach, Ilya Safro

Proceedings of the IEEE International Conference on Quantum Computing and Engineering, 2024

2023

QArchSearch: A Scalable Quantum Architecture Search Package.

Ankit Kulshrestha, Danylo Lykov, Ilya Safro, Yuri Alexeev

CoRR, 2023

Learning To Optimize Quantum Neural Network Without Gradients.

Ankit Kulshrestha, Xiaoyuan Liu, Hayato Ushijima-Mwesigwa, Ilya Safro

CoRR, 2023

QArchSearch: A Scalable Quantum Architecture Search Package.

Ankit Kulshrestha, Ilya Safro, Yuri Alexeev

Proceedings of the SC '23 Workshops of The International Conference on High Performance Computing, 2023

Learning to Optimize Quantum Neural Networks Without Gradients.

Ankit Kulshrestha, Xiaoyuan Liu, Hayato Ushijima-Mwesigwa, Ilya Safro

Proceedings of the IEEE International Conference on Quantum Computing and Engineering, 2023

2022

Cobol2Vec: Learning Representations of Cobol code.

Ankit Kulshrestha, Vishwas Lele

CoRR, 2022

BEINIT: Avoiding Barren Plateaus in Variational Quantum Algorithms.

Ankit Kulshrestha, Ilya Safro

Proceedings of the IEEE International Conference on Quantum Computing and Engineering, 2022

Accelerating COVID-19 Research with Graph Mining and Transformer-Based Learning.

Ilya Tyagin, Ankit Kulshrestha, Justin Sybrandt, Krish Matta, Michael Shtutman, Ilya Safro

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

FAIRLEARN: Configurable and Interpretable Algorithmic Fairness.

Ankit Kulshrestha, Ilya Safro

CoRR, 2021

Coping with Mistreatment in Fair Algorithms.

Ankit Kulshrestha, Ilya Safro

CoRR, 2021

2018

Artificial Intelligence and Deep Learning Applications for Automotive Manufacturing.

André Luckow, Ken Kennedy, Marcin Ziolkowski, Emil Djerekarov, Matthew Cook, Edward B. Duffy, Michael Schleiss, Bennie Vorster, Edwin Weill, Ankit Kulshrestha, Melissa C. Smith

Proceedings of the IEEE International Conference on Big Data (IEEE BigData 2018), 2018