1 citations · 1 across the 6 of their papers we have counts for
6 papers
Bernstein-Vazirani Networks: Quantum Machine Learning by Interference
Natacha Kuete Meli, Tolga Birdal, Prayag Tiwari +2
We introduce Bernstein-Vazirani Networks (BVNs), a non-variational quantum machine learning framework that leverages quantum interference for supervised learning, demonstrated on v…
Layered Quantum Architecture Search for 3D Point Cloud Classification
Natacha Kuete Meli, Jovita Lukasik, Vladislav Golyanik +1
We introduce layered Quantum Architecture Search (layered-QAS), a strategy inspired by classical network morphism that designs Parametrised Quantum Circuit (PQC) architectures by p…
Quantum Multiple Rotation Averaging
Shuteng Wang, Natacha Kuete Meli, Michael Möller +1
Multiple rotation averaging (MRA) is a fundamental optimization problem in 3D vision and robotics that aims to recover globally consistent absolute rotations from noisy relative me…
Quantum-enhanced Computer Vision: Going Beyond Classical Algorithms
Natacha Kuete Meli, Shuteng Wang, Marcel Seelbach Benkner +5
Quantum-enhanced Computer Vision (QeCV) is a new research field at the intersection of computer vision, optimisation theory, machine learning and quantum computing. It has high pot…
Smooth Model Compression without Fine-Tuning
Christina Runkel, Natacha Kuete Meli, Jovita Lukasik +3
Compressing and pruning large machine learning models has become a critical step towards their deployment in real-world applications. Standard pruning and compression techniques ar…
QuCOOP: A Versatile Framework for Solving Composite and Binary-Parametrised Problems on Quantum Annealers
Natacha Kuete Meli, Vladislav Golyanik, Marcel Seelbach Benkner +1
There is growing interest in solving computer vision problems such as mesh or point set alignment using Adiabatic Quantum Computing (AQC). Unfortunately, modern experimental AQC de…