6 papers
Adversarial Data Poisoning Attacks on Quantum Machine Learning in the NISQ Era
Satwik Kundu, Swaroop Ghosh
With the growing interest in Quantum Machine Learning (QML) and the increasing availability of quantum computers through cloud providers, addressing the potential security risks as…
Q-Fusion: Diffusing Quantum Circuits
Collin Beaudoin, Swaroop Ghosh
Quantum computing holds great potential for solving socially relevant and computationally complex problems. Furthermore, quantum machine learning (QML) promises to rapidly improve…
Evaluating Effects of Augmented SELFIES for Molecular Understanding Using QK-LSTM
Collin Beaudoin, Swaroop Ghosh
Identifying molecular properties, including side effects, is a critical yet time-consuming step in drug development. Failing to detect these side effects before regulatory submissi…
Inverse-Transpilation: Reverse-Engineering Quantum Compiler Optimization Passes from Circuit Snapshots
Satwik Kundu, Swaroop Ghosh
Circuit compilation, a crucial process for adapting quantum algorithms to hardware constraints, often operates as a ``black box,'' with limited visibility into the optimization tec…
Dataset Distillation for Quantum Neural Networks
Koustubh Phalak, Junde Li, Swaroop Ghosh
Training Quantum Neural Networks (QNNs) on large amount of classical data can be both time consuming as well as expensive. Higher amount of training data would require higher numbe…
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…