Oceania
NAIS-Net: Stable Deep Networks from Non-Autonomous Differential Equations
Marco Ciccone, Marco Gallieri, Jonathan Masci, Christian Osendorfer, Faustino Gomez
Each block represents atime-invariant iterativeprocess as the first layer in thei-th block,xi(1), is unrolled into a pattern-dependent number,Ki, of processing stages, using weight matricesAi andBi. The skip connections from the input,ui, to all layers in blockimake the process nonautonomous. Blocks can be chained together (each block modeling adifferent latent space) by passing final latentrepresentation,xi(Ki),ofblockiastheinputtoblocki+1.
AccurateLayerwiseInterpretableCompetence Estimation
Our contributions are twofold: First, we establish a statistically rigorous definition of competence that generalizesthecommon notion ofclassifier confidence; second, wepresent theALICE (Accurate Layerwise Interpretable Competence Estimation) Score, a pointwise competence estimator foranyclassifier.