QML-PipeGuard is a framework for runtime behavioral fingerprinting of QML pipelines that absorbs benign drift while detecting adversarial channel substitution via informationally complete measurements.
Potential of quantum computing for drug discovery.IBM Journal of Research and Development, 62(6):6:1–6:20, 2018
2 Pith papers cite this work. Polarity classification is still indexing.
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Empirical benchmark finds hybrid MPI+OpenMP reduces communication overhead and improves efficiency over pure MPI at large node counts for coarse-grained LAMMPS runs.
citing papers explorer
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QML-PipeGuard: Drift-Aware Behavioral Fingerprinting for Quantum Machine Learning Pipeline Integrity
QML-PipeGuard is a framework for runtime behavioral fingerprinting of QML pipelines that absorbs benign drift while detecting adversarial channel substitution via informationally complete measurements.
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Strategies for Molecular Dynamics using Hybrid Systems: LAMMPS Use Case
Empirical benchmark finds hybrid MPI+OpenMP reduces communication overhead and improves efficiency over pure MPI at large node counts for coarse-grained LAMMPS runs.