Daniel D. Scherer

Quantum Natural Policy Gradients: Towards Sample-Efficient Reinforcement Learning

2023 · arXiv (Cornell University)

Reinforcement learning is a growing field in AI with a lot of potential. Intelligent behavior is learned automatically through trial and error in interaction with the environment. However, this learning process is often costly. Using …

Workshop Summary: Quantum Machine Learning

2023

Quantum computing (QC) has made significant progress in recent years, and scientists are exploring its applications across various fields, including quantum machine learning (QML).

BenchQC -- Scalable and modular benchmarking of industrial quantum computing applications

2025 · arXiv (Cornell University)

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 use cases from industry consortium members are the starting point of a …