Introduction: Categorization involves grouping information to make inferences and support novel decisions. In the laboratory, category learning tasks commonly involve ...
Abstract: The generalization of deep neural networks to unknown domains is a major challenge despite their tremendous progress in recent years. For this reason, the dynamic area of domain ...
Deep generative models, including diffusion and flow matching, have shown outstanding performance in synthesizing realistic multi-modal content across images, audio, video, and text. However, the ...
This important modeling work demonstrates out-of-distribution generalization using a grid cell coding scheme combined with an attentional mechanism that operates over these representations ...
Gradient descent-trained neural networks operate effectively even in overparameterized settings with random weight initialization, often finding global optimum solutions despite the non-convex nature ...
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