57 citations · 100 across the 18 of their papers we have counts for
18 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…
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…
Boosting Classification with Quantum-Inspired Augmentations
Matthias Tschöpe, Vitor Fortes Rey, Sogo Pierre Sanon +3
Understanding the impact of small quantum gate perturbations, which are common in quantum digital devices but absent in classical computers, is crucial for identifying potential ad…
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…
Quantum-inspired Embeddings Projection and Similarity Metrics for Representation Learning
Ivan Kankeu, Stefan Gerd Fritsch, Gunnar Schönhoff +3
Over the last decade, representation learning, which embeds complex information extracted from large amounts of data into dense vector spaces, has emerged as a key technique in mac…
DisQu: Investigating the Impact of Disorder in Quantum Generative Models
Yannick Werner, Jasmin Frkatovic, Vitor Fortes Rey +5
Disordered Quantum many-body Systems (DQS) and Quantum Neural Networks (QNN) have many structural features in common. However, a DQS is essentially an initialized QNN with random w…
LLM-Generated Tips Rival Expert-Created Tips in Helping Students Answer Quantum-Computing Questions
Lars Krupp, Jonas Bley, Isacco Gobbi +11
Individual teaching is among the most successful ways to impart knowledge. Yet, this method is not always feasible due to large numbers of students per educator. Quantum computing…
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…
MuJo: Multimodal Joint Feature Space Learning for Human Activity Recognition
Stefan Gerd Fritsch, Cennet Oguz, Vitor Fortes Rey +3
Human activity recognition (HAR) is a long-standing problem in artificial intelligence with applications in a broad range of areas, including healthcare, sports and fitness, securi…
Challenges and Opportunities of Moderating Usage of Large Language Models in Education
Lars Krupp, Steffen Steinert, Maximilian Kiefer-Emmanouilidis +5
The increased presence of large language models (LLMs) in educational settings has ignited debates concerning negative repercussions, including overreliance and inadequate task ref…
Stabilizing an ultracold Fermi gas against Fermi acceleration to superdiffusion through localization
Sian Barbosa, Maximilian Kiefer-Emmanouilidis, Felix Lang +2
Anderson localization, i.e., destructive quantum interference of multiple-scattering paths, halts transport entirely. Contrarily, time-dependent random forces expedite transport vi…
What can we learn from diffusion about Anderson localization of a degenerate Fermi gas?
Sian Barbosa, Maximilian Kiefer-Emmanouilidis, Felix Lang +2
Disorder can fundamentally modify the transport properties of a system. A striking example is Anderson localization, suppressing transport due to destructive interference of propag…
Unreflected Acceptance -- Investigating the Negative Consequences of ChatGPT-Assisted Problem Solving in Physics Education
Lars Krupp, Steffen Steinert, Maximilian Kiefer-Emmanouilidis +5
Large language models (LLMs) have recently gained popularity. However, the impact of their general availability through ChatGPT on sensitive areas of everyday life, such as educati…
Visualizing Entanglement in multi-Qubit Systems
Jonas Bley, Eva Rexigel, Alda Arias +8
In the field of quantum information science and technology, the representation and visualization of quantum states and related processes are essential for both research and educati…
Quantum inspired image augmentation applicable to waveguides and optical image transfer via Anderson Localization
Nikolaos E. Palaiodimopoulos, Vitor Fortes Rey, Matthias Tschöpe +3
We present a quantum inspired image augmentation protocol which is applicable to classical images and, in principle, due to its known quantum formulation applicable to quantum syst…
Excitation transfer in disordered spin chains with long-range exchange interactions
Nikolaos E. Palaiodimopoulos, Maximilian Kiefer-Emmanouilidis, Gershon Kurizki +1
We examine spin excitation or polarization transfer via long-range interacting spin chains with diagonal and off-diagonal disorder. To this end, we determine the mean localization…