2 citations · 3 across the 5 of their papers we have counts for
5 papers
Optimizing Quantum Embedding using Genetic Algorithm for QML Applications
Koustubh Phalak, Archisman Ghosh, Swaroop Ghosh
Quantum Embeddings (QE) are essential for loading classical data into quantum systems for Quantum Machine Learning (QML). The performance of QML algorithms depends on the type of Q…
AltGraph: Redesigning Quantum Circuits Using Generative Graph Models for Efficient Optimization
Collin Beaudoin, Koustubh Phalak, Swaroop Ghosh
Quantum circuit transformation aims to produce equivalent circuits while optimizing for various aspects such as circuit depth, gate count, and compatibility with modern Noisy Inter…
Non-parametric Greedy Optimization of Parametric Quantum Circuits
Koustubh Phalak, Swaroop Ghosh
The use of Quantum Neural Networks (QNN) that are analogous to classical neural networks, has greatly increased in the past decade owing to the growing interest in the field of Qua…
Quantum Random Access Memory For Dummies
Koustubh Phalak, Avimita Chatterjee, Swaroop Ghosh
Quantum Random Access Memory (QRAM) has the potential to revolutionize the area of quantum computing. QRAM uses quantum computing principles to store and modify quantum or classica…
Shot Optimization in Quantum Machine Learning Architectures to Accelerate Training
Koustubh Phalak, Swaroop Ghosh
In this paper, we propose shot optimization method for QML models at the expense of minimal impact on model performance. We use classification task as a test case for MNIST and FMN…