Deep learning has triggered the current rise of artificial intelligence and is the workhorse of today’s machine intelligence. Numerous success stories have rapidly spread all over science, industry and society, but its limitations have only recently come into focus. In this Perspective we seek to ...
We use concept-based interpretable models to mitigate shortcut learning. Existing methods lack interpretability. Beginning with a Blackbox, we iteratively carve out a mixture of interpretable experts (MoIE) and a residual network. Each expert explains a subset of data using First Order Logic (FOL...
Deep learning 1. Introduction “If you would only recognize that life is hard, things would be so much easier for you.”—Louis D. Brandeis Deep convolutional neural networks (DCNNs) have achieved notable success in image recognition, sometimes achieving human-level performance or even surpassing...
Shortcut learning occurs when a deep neural network overly relies on spurious correlations in the training dataset in order to solve downstream tasks. Prior works have shown how this impairs the compositional generalization capability of deep learning models. To address this problem, we propose a ...
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We show, based on the following three grounds, that the primary visual cortex (V1) is a biological direct-shortcut deep residual learning neural network (ResNet) for sparse visual processing: (1) We first highlight that Gabor-like sets of basis functions, which are similar to the receptive...
Residual Network (ResNet) is undoubtedly a milestone in deep learning. ResNet is equipped with shortcut connections between layers, and exhibits efficient training using simple first order algorithms. Despite of the great empirical success, the reason behind is far from being well understood. In ...
Deep learningComputer visionUnderwater object detectionConvolutional neural network is a prominent innovation in computer vision but is often troubled by problems such as dark light, turbidity, blur and high similarity to the background when applied to underwater object detection. Underwater object ...
Deep neural networks have demonstrated remarkable performance in medical image analysis. However, its susceptibility to spurious correlations due to shortcut learning raises concerns about network interpretability and reliability. Furthermore, shortcut learning is exacerbated in medical contexts where disease ...
MachineLearningModel MacroInternal MacroPrivate MacroProtected MacroPublic MacroSealed MacroShortcut MageProduct MagicWand MainMenuControl Makefile MakefileApplication MakeSameHeight ManageCounterSets ManifestFile ManualTest ManyToMany MapInternal MapItemInternal MapItemPrivate MapItemProtected MapItemPublic MapItemSe...