Top-level human players perform about 350 actions per minute [1].

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We develop and test two potential solutions: an alternate validation method ("sample validation") and a novel regularization method ("coordinated dropout").

Exten-sive experiments show the effectiveness of this measure to rank different GANmodels and capture the typical GAN failure scenarios, including mode collapse andnon-convergentbehaviours.

In the preliminary "Res3D+ConvLSTM+MobileNet" architecture, the blocks 1-4 of Res3D [16] are used first to learn the local short-term spatiotemporal feature maps which have a relativelylargespatialsize.

Byaproperscalingofthedistance, ourproposed Maximum Concept Matching (MCM) scoreachievesstrong ID-OODseparability (see Figure 1). Thereexistsoverlappingregions (shown w); Right: Cosinesimilaritiesbetween OODinIDconceptvectors.

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