59 citations · 224 across the 62 of their papers we have counts for
9 papers · 1 filter
QuBLAST: A Framework for Quantizing Large Language Models with Block-Level Compression Approach and Activation Scaling Strategy
Pasindu Wickramasinghe, Achyuta Muthuvelan, Rachmad Vidya Wicaksana Putra +2
LLMs have become the state-of-the-art algorithms for solving NLP tasks. However, they typically come at huge computational and memory costs, thus making them difficult to deploy on…
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…
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…
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…
IQNN-CS: Interpretable Quantum Neural Network for Credit Scoring
Abdul Samad Khan, Nouhaila Innan, Aeysha Khalique +1
Credit scoring is a high-stakes task in financial services, where model decisions directly impact individuals' access to credit and are subject to strict regulatory scrutiny. While…
KASPER: Kolmogorov Arnold Networks for Stock Prediction and Explainable Regimes
Vidhi Oad, Param Pathak, Nouhaila Innan +2
Forecasting in financial markets remains a significant challenge due to their nonlinear and regime-dependent dynamics. Traditional deep learning models, such as long short-term mem…
Neuromorphic Computing for Embodied Intelligence in Autonomous Systems: Current Trends, Challenges, and Future Directions
Alberto Marchisio, Muhammad Shafique
The growing need for intelligent, adaptive, and energy-efficient autonomous systems across fields such as robotics, mobile agents (e.g., UAVs), and self-driving vehicles is driving…
QFAL: Quantum Federated Adversarial Learning
Walid El Maouaki, Nouhaila Innan, Alberto Marchisio +3
Quantum federated learning (QFL) merges the privacy advantages of federated systems with the computational potential of quantum neural networks (QNNs), yet its vulnerability to adv…
MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks
Lotfi Abdelkrim Mecharbat, Alberto Marchisio, Muhammad Shafique +2
There has been a surge in optimizing edge Deep Neural Networks (DNNs) for accuracy and efficiency using traditional optimization techniques such as pruning, and more recently, empl…