1 citations · 1 across the 3 of their papers we have counts for
3 papers
Model selection in hybrid quantum neural networks with applications to quantum transformer architectures
Harsh Wadhwa, Rahul Bhowmick, Naipunnya Raj +3
Quantum machine learning models generally lack principled design guidelines, often requiring full resource-intensive training across numerous choices of encodings, quantum circuit…
Quantum Generative Adversarial Autoencoders: Learning latent representations for quantum data generation
Naipunnya Raj, Rajiv Sangle, Avinash Singh +1
In this work, we introduce the Quantum Generative Adversarial Autoencoder (QGAA), a quantum model for generation of quantum data. The QGAA consists of two components: (a) Quantum A…
Parallelizing Quantum-Classical Workloads: Profiling the Impact of Splitting Techniques
Tuhin Khare, Ritajit Majumdar, Rajiv Sangle +3
Quantum computers are the next evolution of computing hardware. Quantum devices are being exposed through the same familiar cloud platforms used for classical computers, and enabli…