1 citations · 1 across the 27 of their papers we have counts for
29 papers
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…
Q-PhotoMarket: A Design Space Exploration Framework for Photonic Hybrid Quantum Neural Networks in Financial Market Prediction
Alberto Marchisio, Hanzalah Mohamed Siraj, Muhammad Kashif +2
Photonic quantum computing has recently emerged as a promising platform for hybrid quantum machine learning due to its native realization of linear-optical circuits and the computa…
QSTAR: Quantum Selective Transfer with Adaptive Routing
Saim Rehman, Nouhaila Innan, Muhammad Shafique
Quantum transfer learning (QTL) is often evaluated by replacing a classical classifier with a fixed variational quantum head, but this hides a key question: when is the quantum bra…
PN-QNN: Harnessing Physical Noise as a Native Regularizer in Photonic Hybrid Quantum Neural Networks
Farah Elnakhal, Alberto Marchisio, Nouhaila Innan +2
Physical noise in near-term quantum hardware is usually treated as a nuisance to suppress. We ask whether it can instead act as a hardware-native regularizer for photonic hybrid qu…
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…
Quantum Reservoir Computing for Short-Term Power Load Forecasting in Resource-Constrained Energy Systems
Mansi Od, Param Pathak, Nouhaila Innan +1
Short-term load forecasting is essential for reliable energy management, but practical deployment on edge devices requires models that remain accurate under limited memory, finite…
QPredSGG: Hybrid Quantum Predicate Learning for Long-Tailed Scene Graph Generation
Prerana Ramkumar, Nouhaila Innan, Muhammad Shafique
Scene Graph Generation (SGG) requires relational reasoning over objects and their interactions, but performance is constrained by long-tail predicate imbalance. Classical SGG model…
Game, Set, Quantum: Parameterized Quantum Circuit for Correlated Equilibrium in Bayesian Games
Param Pathak, Vidhi Oad, Nouhaila Innan +2
Strategic decision-making among many agents under incomplete information is central to economics, security, and multi-agent artificial intelligence (AI). Computing equilibria in su…
Meta-Quantum Ensemble Framework for Robust Network Intrusion Detection
Ritvik Bhatnagar, Nouhaila Innan, Angel Arul Jothi J. +1
Intrusion Detection Systems (IDSs) must maintain high detection sensitivity while operating under strict false-positive constraints, a challenge intensified by class imbalance and…
Q-SYNTH: Hybrid Quantum-Classical Adversarial Augmentation for Imbalanced Fraud Detection
Adam Innan, Mansour El Alami, Nouhaila Innan +2
Credit card fraud detection is fundamentally challenged by extreme class imbalance, where fraudulent transactions are rare yet operationally critical. This imbalance often biases s…
Towards Fair Benchmarking of Quantum Transfer Learning for Visual Classification
Nouhaila Innan, Saim Rehman, Muhammad Shafique
Quantum Transfer Learning (QTL) offers a promising approach for visual quantum machine learning under near-term constraints, where limited qubit counts, shallow circuit depths, and…
Hybrid Quantum-Classical Neural Architecture Search
Alberto Marchisio, Muhammad Kashif, Nouhaila Innan +1
Hybrid quantum-classical neural networks (HQNNs) are emerging as a practical approach for quantum machine learning in the noisy intermediate-scale quantum (NISQ) era, as they combi…
HQTN-SER: Speech Emotion Recognition with Hybrid Quantum Tensor Networks
Mahad Mohtashim, Nouhaila Innan, Muhammad Shafique
Speech emotion recognition (SER) remains fragile in real-world conditions because emotional cues are subtle, speaker-dependent, and easily confounded by recording variability, whil…
EFaaS: A Quantum-Classical Serverless Entangled Scheduler for Hybrid Variational Algorithms
Abolfazl Younesi, Nouhaila Innan, Alberto Marchisio +1
As quantum computing enters the Utility Era, realizing near-term advantage relies heavily on Hybrid Variational Quantum Algorithms (VQAs). These algorithms require a tightly couple…
PennySynth: RAG-Driven Data Synthesis for Automated Quantum Code Generation
Minghao Shao, Nouhaila Innan, Hariharan Janardhanan +3
The growing complexity of quantum programming frameworks has exposed a critical limitation in existing large language model (LLM)-based code assistants: general-purpose models hall…
Enhancing Blood Cells Classification using Hybrid Quantum Neural Networks
Guilherme Cruz, Nouhaila Innan, Alberto Marchisio +2
Accurate classification of microscopic blood cells is still a critical task in medical image analysis, where subtle variations and limited data can challenge conventional deep lear…
Q-PhotoNAS: Hybrid Quantum Neural Architecture Search Framework on Photonic Devices
Farah Elnakhal, Alberto Marchisio, Nouhaila Innan +2
Photonic quantum computing is a promising platform for scalable quantum machine learning, but designing effective hybrid architectures remains challenging under hardware and optimi…
A2QTGN: Adaptive Amplitude Quantum-Integrated Temporal Graph Network for Dynamic Link Prediction
Nouhaila Innan, M. Murali Karthick, Simeon Kandan Sonar +2
Dynamic link prediction is important for modeling evolving interactions in social, communication, financial, and transportation networks. Classical temporal graph models capture ch…
Q-SpiRL: Quantum Spiking Reinforcement Learning for Adaptive Robot Navigation
Mohamed Khair Altrabulsi, Nouhaila Innan, Alberto Marchisio +2
Adaptive robot navigation in dynamic environments requires policies that can reach the target reliably while producing efficient and stable trajectories. This paper presents Q-SpiR…
QLIF-CAST: Quantum Leaky-Integrate-and-Fire for Time-Series Weather Forecasting
Alberto Marchisio, Aayan Ebrahim, Nouhaila Innan +2
Accurate and efficient time-series forecasting remains a challenging problem for both classical and quantum neural architectures, particularly in multivariate environmental setting…
How Embeddings Shape Graph Neural Networks: Classical vs Quantum-Oriented Node Representations
Nouhaila Innan, Antonello Rosato, Alberto Marchisio +1
Node embeddings act as the information interface for graph neural networks, yet their empirical impact is often reported under mismatched backbones, splits, and training budgets. T…
GAT-QNN: Genetic Algorithm-Based Training of Hybrid Quantum Neural Networks
Tasnim Ahmed, Alberto Marchisio, Muhammad Kashif +2
Hybrid Quantum Neural Networks (HQNNs) combine classical learning with parameterized quantum circuits, but their practical performance is often limited by (i) the noise of Noisy In…
Design Space Exploration of Hybrid Quantum Neural Networks for Chronic Kidney Disease
Muhammad Kashif, Hanzalah Mohamed Siraj, Nouhaila Innan +2
Hybrid Quantum Neural Networks (HQNNs) have recently emerged as a promising paradigm for near-term quantum machine learning. However, their practical performance strongly depends o…
SPATE: Spiking-Phase Adaptive Temporal Encoding for Quantum Machine Learning
Nouhaila Innan, Rachmad Vidya Wicaksana Putra, Muhammad Shafique
Most quantum machine learning (QML) pipelines still rely on static encodings such as angle and amplitude maps, and this limits their ability to handle temporal information. To addr…