551 citations · 568 across the 10 of their papers we have counts for
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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…
Meta-learning of Gibbs states for many-body Hamiltonians with applications to Quantum Boltzmann Machines
Ruchira V Bhat, Rahul Bhowmick, Avinash Singh +1
The preparation of quantum Gibbs states is a fundamental challenge in quantum computing, essential for applications ranging from modeling open quantum systems to quantum machine le…
Enhancing variational quantum algorithms by balancing training on classical and quantum hardware
Rahul Bhowmick, Harsh Wadhwa, Avinash Singh +3
Quantum computers offer a promising route to tackling problems that are classically intractable such as in prime-factorization, solving large-scale linear algebra and simulating co…