L3S Research Center

Stochastic neural networks for quantum devices

Abstract This work presents a formulation to express and optimize stochastic neural networks as quantum circuits in gate-based quantum computing. Motivated by a classical perceptron, stochastic artificial neurons are introduced and combined into a quantum neural network. The Kief...

Refining the average µ182W and µ142Nd compositions of the Archean to Proterozoic upper crust

The chemical composition of siliciclastic rocks provided key insights into the chemical composition of the upper continental crust and was suggested to record the onset of modern-style plate tectonics by ∼3.0 Ga. Recent studies aiming to establish the crustal µ 182 W and µ 142 Nd...

BeVerA-KG: Behaviour-Driven Design-Time Verification of Neuro-Symbolic Agents via Knowledge Graphs for Trustworthy Humanitarian Edge Systems

Runtime guardrails for LLM agents enforce safety per individual action at execution time, but fail to verify the reachable state space before deployment. We present BeVerA-KG, a behaviour-driven framework that shifts verification to design time. Stakeholder-authored Gherkin scena...

Model-based comparison of latency estimation methods for the pupillary light reflex

Abstract Accurate estimation of pupillary light reflex (PLR) latency is important in clinical and research settings, yet reported results are often difficult to compare due to differences in hardware, sampling rates, and analysis methods. This study introduces a systematic and re...