1 citations · 1 across the 7 of their papers we have counts for
8 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 Implicit Neural Representations for Novel View Synthesis
Daniele Lizzio Bosco, Shuteng Wang, Giuseppe Serra +1
Quantum implicit neural representations have recently emerged as compact function approximators for continuous visual signals. In parallel, Neural Radiance Fields (NeRFs) have beco…
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…
Projected Stochastic Gradient Descent with Quantum Annealed Binary Gradients
Maximilian Krahn, Michele Sasdelli, Fengyi Yang +4
We present, QP-SBGD, a novel layer-wise stochastic optimiser tailored towards training neural networks with binary weights, known as binary neural networks (BNNs), on quantum hardw…
Q-FW: A Hybrid Classical-Quantum Frank-Wolfe for Quadratic Binary Optimization
Alp Yurtsever, Tolga Birdal, Vladislav Golyanik
We present a hybrid classical-quantum framework based on the Frank-Wolfe algorithm, Q-FW, for solving quadratic, linearly-constrained, binary optimization problems on quantum annea…
Convex Joint Graph Matching and Clustering via Semidefinite Relaxations
Maximilian Krahn, Florian Bernard, Vladislav Golyanik
This paper proposes a new algorithm for simultaneous graph matching and clustering. For the first time in the literature, these two problems are solved jointly and synergetically w…