26 citations · 44 across the 20 of their papers we have counts for
5 papers · 2 filters
The Dilemma of Random Parameter Initialization and Barren Plateaus in Variational Quantum Algorithms
Muhammad Kashif, Muhammad Shafique
This paper presents an easy-to-implement approach to mitigate the challenges posed by barren plateaus (BPs) in randomly initialized parameterized quantum circuits (PQCs) within var…
Computational Advantage in Hybrid Quantum Neural Networks: Myth or Reality?
Muhammad Kashif, Alberto Marchisio, Muhammad Shafique
Hybrid Quantum Neural Networks (HQNNs) have gained attention for their potential to enhance computational performance by incorporating quantum layers into classical neural network…
Cutting is All You Need: Execution of Large-Scale Quantum Neural Networks on Limited-Qubit Devices
Alberto Marchisio, Emman Sychiuco, Muhammad Kashif +1
The rapid advancement in Quantum Computing, particularly through Noisy-Intermediate Scale Quantum (NISQ) devices, has spurred significant interest in Quantum Machine Learning (QML)…
Investigating the Effect of Noise on the Training Performance of Hybrid Quantum Neural Networks
Muhammad Kashif, Emman Sychiuco, Muhammad Shafique
In this paper, we conduct a comprehensively analyze the influence of different quantum noise gates, including Phase Flip, Bit Flip, Phase Damping, Amplitude Damping, and the Depola…
HQNET: Harnessing Quantum Noise for Effective Training of Quantum Neural Networks in NISQ Era
Muhammad Kashif, Muhammad Shafique
Effective training of Quantum Neural Networks (QNNs) is crucial in the Noisy Intermediate-Scale Quantum (NISQ) era, where noise accelerates the onset of barren plateaus (BPs) and l…