6 citations · 8 across the 4 of their papers we have counts for
4 papers
The Average Relative Entropy and Transpilation Depth determines the noise robustness in Variational Quantum Classifiers
Aakash Ravindra Shinde, Arianne Meijer - van de Griend, Jukka K. Nurminen
Variational Quantum Algorithms (VQAs) have been extensively researched for applications in Quantum Machine Learning (QML), Optimization, and Molecular simulations. Although designe…
Influence of Data Dimensionality Reduction Methods on the Effectiveness of Quantum Machine Learning Models
Aakash Ravindra Shinde, Jukka K. Nurminen
Data dimensionality reduction techniques are often utilized in the implementation of Quantum Machine Learning models to address two significant issues: the constraints of NISQ quan…
Perspectives on Utilization of Measurements in Quantum Algorithms
Valter Uotila, Ilmo Salmenperä, Leo Becker +3
Measurement is a fundamental operation in quantum computing and has many important use cases in quantum algorithms. This article provides a comprehensive overview of the basic meas…
A Post-Training Approach for Mitigating Overfitting in Quantum Convolutional Neural Networks
Aakash Ravindra Shinde, Charu Jain, Amir Kalev
Quantum convolutional neural network (QCNN), an early application for quantum computers in the NISQ era, has been consistently proven successful as a machine learning (ML) algorith…