Deep Learning
New computational algorithms make it possible to build neural networks with many input nodes and many layers, and distinguish "deep learning" of these networks from previous work on artificial neural nets.
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Finding Differences Between Transformers and ConvNets Using Counterfactual Simulation Testing
Neural Information Processing Systems
Modern deep neural networks tend to be evaluated on static test sets.
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PerturbationLearningBasedAnomalyDetection
Neural Information Processing Systems
There are a few approaches to building deep anomaly detection objectives or models.
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