10 papers
KAN-MLP-Mixer: A comprehensive investigation of the usage of Kolmogorov-Arnold Networks (KANs) for improving IMU-based Human Activity Recognition
Mengxi Liu, Sizhen Bian, Vitor Fortes +5
Kolmogorov-Arnold Networks (KANs) have demonstrated an exceptional ability to learn complex functions on clean, low-dimensional data but struggle to maintain performance on noisy a…
On the Generalization Limits of Quantum Generative Adversarial Networks with Pure State Generators
Jasmin Frkatovic, Akash Malemath, Ivan Kankeu +7
We investigate the capabilities of Quantum Generative Adversarial Networks (QGANs) in image generations tasks. Our analysis centers on fully quantum implementations of both the gen…
Visualization enhances Problem Solving in multi-Qubit Systems
Jonas Bley, Eva Rexigel, Alda Arias +7
Quantum Information Science (QIS) is a vast, diverse, and abstract field. In consequence, learners face many challenges. Science, Technology, Engineering, and Mathematics (STEM) ed…
Visualizing Quantum States: A Pilot Study on Problem Solving in Quantum Information Science Education
Jonas Bley, Eva Rexigel, Alda Arias +8
In the rapidly evolving interdisciplinary field of quantum information science and technology, a major obstacle is the need to understand advanced mathematics to solve complex prob…
No Scratch Quantum Computing by Reducing Qubit Overhead for Efficient Arithmetics
Omid Faizy, Norbert Wehn, Paul Lukowicz +1
Quantum arithmetic computation requires a substantial number of scratch qubits to stay reversible. These operations necessitate qubit and gate resources equivalent to those needed…
QuKAN: A Quantum Circuit Born Machine approach to Quantum Kolmogorov Arnold Networks
Yannick Werner, Akash Malemath, Mengxi Liu +4
Kolmogorov Arnold Networks (KANs), built upon the Kolmogorov Arnold representation theorem (KAR), have demonstrated promising capabilities in expressing complex functions with fewe…