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A station-guided framework for high-resolution PM downscaling over Europe that recovers fine-grained spatial structures and effectively mitigates localised CAMS biases and introduces a time-agnostic propagation strategy that utilises spatial Gaussian blending of interpolated OpenAQ observations.
TESTNAV prioritises severe yet realistic failures by formulating robustness testing as bi-objective optimisation: maximise performance degradation while preserving input fidelity measured by modality-specific metrics.
TestifAI, a deep learning testing framework for efficient and accurate estimation of robustness against combinations of perturbations, is proposed and partial model tomography is introduced, a novel approach to reconstructing model behaviour in a multi-perturbation space from tests that apply only a small number of per...
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