10 papers
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…
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…
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…
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…
Practical Quantum-Classical Feature Fusion for complex data Classification
Azadeh Alavi, Fatemeh Kouchmeshki, Abdolrahman Alavi
Hybrid quantum and classical learning aims to couple quantum feature maps with the robustness of classical neural networks, yet most architectures treat the quantum circuit as an i…
Quantum Semi-Random Forests for Qubit-Efficient Recommender Systems
Azadeh Alavi, Fatemeh Kouchmeshki, Abdolrahman Alavi +2
Modern recommenders describe each item with hundreds of sparse semantic tags, yet most quantum pipelines still map one qubit per tag, demanding well beyond one hundred qubits, far…
A Geometric-Aware Perspective and Beyond: Hybrid Quantum-Classical Machine Learning Methods
Azadeh Alavia, Hossein Akhoundib, Fatemeh Kouchmeshkib +4
Geometric Machine Learning (GML) has shown that respecting non-Euclidean geometry in data spaces can significantly improve performance over naive Euclidean assumptions. In parallel…
Analyzing Advanced AI Systems Against Definitions of Life and Consciousness
Azadeh Alavi, Hossein Akhoundi, Fatemeh Kouchmeshki
Could artificial intelligence ever become truly conscious in a functional sense; this paper explores that open-ended question through the lens of Life, a concept unifying classical…