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20232026
most citedAlleviating Barren Plateaus in Parameterized Quantum Machine Learning Circuits: Investigating Advanced Parameter Initialization Strategies

26 citations · 44 across the 20 of their papers we have counts for

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Showing 2026 · quant-phShow all

8 papers · 2 filters

quant-ph2026

QBFF: Deep Quantum Bottleneck for Automatic Speaker Verification Anti-Spoofing

Anton Firc, Nouhaila Innan, Vojtěch Staněk +6

A central goal of quantum machine learning is to identify applications in which small quantum circuits can improve task performance while remaining executable on real hardware. We…

quant-ph2026

VQCSim: When Does Compile-Once Statevector Simulation Beat Generic Quantum Frameworks?

Anton Firc, Martin Perešíni, Vojtěch Mrázek +7

Hybrid quantum-classical machine learning workflows repeatedly evaluate many small parametrized circuits during training and model exploration. In this regime, framework dispatch a…

quant-ph2026

Late Breaking Results: Hardware-Aware Compilation Reshapes Trainability in Variational Quantum Circuits

Muhammad Kashif, Muhammad Shafique

Variational quantum circuits (VQCs) are typically evaluated at the logical design level when analyzing trainability. However, execution on real quantum devices requires hardware-aw…

quant-ph2026

Q-RAIL: A Reliability-Aware Framework for Quantum Federated Learning on Heterogeneous Noisy Hardware

Walid El Maouaki, Muhammad Shafique

Quantum federated learning (QFL) on NISQ hardware is highly sensitive to backend heterogeneity: some clients contribute informative updates, while others contribute noise-dominated…

quant-ph2026

Rethinking Expressibility-Trainability Trade-off in Hybrid Quantum Neural Networks

Muhammad Kashif, Muhammad Shafique

Hybrid quantum neural networks (HQNNs) integrate parameterized quantum circuits (PQCs) within classical networks, where the behavior of the underlying PQCs is often the primary foc…

quant-ph2026

QGCL: Quantum-Guided Clause Learning for Cryptanalytic SAT

Walid El Maouaki, Alberto Marchisio, Muhammad Shafique

Power side-channel attacks on AES exploit data-dependent physical leakage to recover secret keys, but turning noisy leakage observations into a verified AES-128 key remains a hard…

quant-ph2026

Q-LEAK: Quantum-Based LEAKage Verification for Side-Channel Countermeasures

Walid El Maouaki, Alberto Marchisio, Muhammad Shafique

Formal verification of power side-channel leakage and its countermeasures in cryptographic algorithms is challenging, as SAT-based methods fail to scale on XOR-heavy, time-unrolled…

quant-ph2026

Beyond Logical Circuits: Hardware-Aware Analysis of Expressibility and Trainability in Variational Quantum Algorithms

Muhammad Kashif, Muhammad Shafique

Variational quantum algorithms (VQAs) rely on parameterized quantum circuits (PQCs), whose performance is governed by expressibility and trainability. Existing studies typically ev…