9 citations · 25 across the 11 of their papers we have counts for
11 papers
Quantum State Preparation via Neural Network Encoding in Quantum Machine Learning
Kevin W. Aoun, Florian J. Kiwit, Carlos A. Riofrío +4
A central challenge in quantum machine learning is the state preparation bottleneck that describes the prohibitive computational cost of loading high-dimensional classical data int…
Hybrid Quantum-HPC Middleware Systems for Adaptive Resource, Workload and Task Management
Pradeep Mantha, Florian J. Kiwit, Nishant Saurabh +2
Hybrid quantum-classical applications pose significant resource management challenges due to heterogeneity and dynamism in both infrastructure and workloads. Quantum-HPC environmen…
Scaling Quantum Machine Learning without Tricks: Full-Resolution and Diverse Image Generation
Jonas Jäger, Florian J. Kiwit, Carlos A. Riofrío
Quantum generative modeling is a rapidly evolving discipline at the intersection of quantum computing and machine learning. Contemporary quantum machine learning is generally limit…
Typical Machine Learning Datasets as Low-Depth Quantum Circuits
Florian J. Kiwit, Bernhard Jobst, Andre Luckow +2
Quantum machine learning (QML) is an emerging field that investigates the capabilities of quantum computers for learning tasks. While QML models can theoretically offer advantages…
BenchQC -- Scalable and modular benchmarking of industrial quantum computing applications
Florian Geissler, Eric Stopfer, Christian Ufrecht +19
We present BenchQC, a research project funded by the state of Bavaria, which promotes an application-centric perspective for benchmarking real-world quantum applications. Diverse u…
Quantum Computing for Automotive Applications
Carlos A. Riofrío, Johannes Klepsch, Jernej Rudi Finžgar +7
Quantum computing could impact various industries, with the automotive industry with many computational challenges, from optimizing supply chains and manufacturing to vehicle engin…
Quantum Mini-Apps: A Framework for Developing and Benchmarking Quantum-HPC Applications
Nishant Saurabh, Pradeep Mantha, Florian J. Kiwit +2
With the increasing maturity and scale of quantum hardware and its integration into HPC systems, there is a need to develop robust techniques for developing, characterizing, and be…
Towards Application-Aware Quantum Circuit Compilation
Nils Quetschlich, Florian J. Kiwit, Maximilian A. Wolf +4
Quantum computing has made tremendous improvements in both software and hardware that have sparked interest in academia and industry to realize quantum computing applications. To t…
Benchmarking Quantum Generative Learning: A Study on Scalability and Noise Resilience using QUARK
Florian J. Kiwit, Maximilian A. Wolf, Marwa Marso +4
Quantum computing promises a disruptive impact on machine learning algorithms, taking advantage of the exponentially large Hilbert space available. However, it is not clear how to…
Application-Oriented Benchmarking of Quantum Generative Learning Using QUARK
Florian J. Kiwit, Marwa Marso, Philipp Ross +3
Benchmarking of quantum machine learning (QML) algorithms is challenging due to the complexity and variability of QML systems, e.g., regarding model ansatzes, data sets, training t…
Pooling techniques in hybrid quantum-classical convolutional neural networks
Maureen Monnet, Hanady Gebran, Andrea Matic-Flierl +4
Quantum machine learning has received significant interest in recent years, with theoretical studies showing that quantum variants of classical machine learning algorithms can prov…