Following unprecedented success on the natural language tasks, Transformers have been
successfully applied to several computer vision problems, achieving state-of-the-art results …

Artificial neural networks (ANNs) inspired by biology are beginning to be widely used to
model behavioural and neural data, an approach we call 'neuroconnectionism'. ANNs have …

We revisit large kernel design in modern convolutional neural networks (CNNs). Inspired by
recent advances in vision transformers (ViTs), in this paper, we demonstrate that using a few …

Transformer, the model of choice for natural language processing, has drawn scant attention
from the medical imaging community. Given the ability to exploit long-term dependencies …

Dense computer vision tasks such as object detection and segmentation require effective
multi-scale feature representation for detecting or classifying objects or regions with varying …

Vision transformers (ViT) have demonstrated impressive performance across numerous
machine vision tasks. These models are based on multi-head self-attention mechanisms that …

Transformer, the model of choice for natural language processing, has drawn scant attention
from the medical imaging community. Given the ability to exploit long-term dependencies …

Large-kernel convolutional neural networks (ConvNets) have recently received extensive
research attention but two unresolved and critical issues demand further investigation. 1) …

A few years ago, the first CNN surpassed human performance on ImageNet. However, it
soon became clear that machines lack robustness on more challenging test cases, a major …

Mental representations remain the central posits of psychology after many decades of
scrutiny. However, there is no consensus about the representational format (s) of biological …