3 citations · 4 across the 17 of their papers we have counts for
9 papers · 1 filter
When do quantum views help? Complementary classical-quantum representations in multi-view fusion
Azadeh Alavi, Fatemeh Kouchmeshki, Hossein Akhoundi +3
Recent studies have reported promising results from quantum machine learning in drug discovery, healthcare, materials science and cybersecurity. Research includes comparisons with…
DreamQAS: Learning a Decision-Useful World Model for VQE-Efficient Quantum Architecture Search
Jiayang Niu, Yan Wang, Jie Li +4
Reinforcement-learning-based quantum architecture search (RL-QAS) repeatedly invokes a variational quantum eigensolver (VQE) after each gate addition even though circuit transition…
Gram-Certified Resource Continuation for Structured Quantum Representation Audits
Azadeh Alavi, Fatemeh Kouchmeshki, Hossein Akhoundi +1
Dense representation of an -qubit pure state requires complex amplitudes, precluding dense classical materialization at large . We develop Gram-certified resource conti…
Invariance Audits for Quantum Kernels and Variational Rewinding: A Real-to-Hermitian Taxonomy of Projector, Flag, Anchor, and Density Geometry
Azadeh Alavi, Fatemeh Kouchmeshki, Hossein Akhoundi
Machine-learning models often replace vectors by normalized directions, projectors, covariances, subspaces, ordered flags, quantum states, or density operators before any classifie…
Energy Accuracy Is Not Enough: A Structure-Aware Benchmark and Evaluation Protocol for Quantum Architecture Search
Jiayang Niu, Akib Karim, Yan Wang +5
Quantum architecture search for molecular ground-state estimation is commonly evaluated through energy accuracy, which does not describe circuit cost or the physical properties of…
A Givens-exchange ansatz for molecular variational eigensolvers
Azadeh Alavi, Fatemeh Kouchmeshki, Muhammad Usman +4
Molecular ground-state energies help determine conformer rankings, reaction energetics, and electronic effects in computational drug discovery, but accurate calculations become dif…
QBioFusion-QSAR: Morgan-Anchored Quantum Multiple Kernel Learning for Small-Data Ligand Classification
Azadeh Alavi, Fatemeh Kouchmeshki, Muhammad Usman +1
Small quantitative structure-activity relationship (QSAR) studies are difficult when close molecular analogues have different activity labels. This paper asks whether a quantum ker…
Certified vs. Empirical Adversarial Robust-ness via Hybrid Convolutions with Attention Stochasticity
Joy Dhar, Song Xia, Manish Kumar Pandey +5
We introduce Hybrid Convolutions with Attention Stochasticity (HyCAS), an adversarial defense that narrows the long-standing gap between provable robustness under L2 certificates a…
Geometric and Quantum Kernel Methods for Predicting Skeletal Muscle Outcomes in chronic obstructive pulmonary disease
Azadeh Alavi, Hamidreza Khalili, Stanley H. Chan +3
Chronic obstructive pulmonary disease (COPD) affects hundreds of millions of people worldwide, and skeletal-muscle dysfunction is clinically important. Quantum machine learning is…