22 citations · 22 across the 6 of their papers we have counts for
6 papers
Moment-Structured Block Encodings of Periodic Finite-Difference Operators
Jishnu Mahmud, Rebekah Herrman
Block encoding is the standard technique for accessing matrix data in quantum linear-algebra algorithms. Its implementation directly affects its subnormalization, which in turn con…
Explicit Block Encoding of Difference-of-Gaussian Operators on a Periodic Grid
Jishnu Mahmud, John Winship, Tom Lash +2
The Difference-of-Gaussian (DoG) is a widely used operator across applications, including image processing (feature and edge detection), quantum machine learning, and finite-differ…
Hybrid Quantum-Classical Learning for Multiclass Image Classification
Shuchismita Anwar, Sowmitra Das, Muhammad Iqbal Hossain +1
This study explores the challenge of improving multiclass image classification through quantum machine-learning techniques. It explores how the discarded qubit states of Noisy Inte…
Selective Feature Re-Encoded Quantum Convolutional Neural Network with Joint Optimization for Image Classification
Shaswata Mahernob Sarkar, Sheikh Iftekhar Ahmed, Jishnu Mahmud +2
Quantum Machine Learning (QML) has seen significant advancements, driven by recent improvements in Noisy Intermediate-Scale Quantum (NISQ) devices. Leveraging quantum principles su…
Patch-Based End-to-End Quantum Learning Network for Reduction and Classification of Classical Data
Jishnu Mahmud, Shaikh Anowarul Fattah
In the noisy intermediate scale quantum (NISQ) era, the control over the qubits is limited due to the errors caused by quantum decoherence, crosstalk, and imperfect calibration. He…
Quantum Convolutional Neural Networks with Interaction Layers for Classification of Classical Data
Jishnu Mahmud, Raisa Mashtura, Shaikh Anowarul Fattah +1
Quantum Machine Learning (QML) has come into the limelight due to the exceptional computational abilities of quantum computers. With the promises of near error-free quantum compute…