SPUNA leverages spectral neighborhood annotation on visual feature manifolds to enable robust PU learning for covariate shift detection, matching fully supervised performance.
Probabilistic modeling of deep features for out-of-distribution and adversarial detection
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Deep learning on information-rich scientific images collapses to one-dimensional predictions due to a mismatch between data priors and the model's simplicity bias, even after robustification techniques.
citing papers explorer
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From Local Geometry to Global Pseudo Labeling for Robust Positive Unlabeled Learning under Covariate Shift
SPUNA leverages spectral neighborhood annotation on visual feature manifolds to enable robust PU learning for covariate shift detection, matching fully supervised performance.
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Anatomy of a failure: When, how, and why deep vision fails in scientific domains
Deep learning on information-rich scientific images collapses to one-dimensional predictions due to a mismatch between data priors and the model's simplicity bias, even after robustification techniques.