Neuroscientists have long characterized the properties and functions of the nervous system,
and are increasingly succeeding in answering how brains perform the tasks they do. But the …

Making inferences from behaviour to cognition is problematic due to a many-to-one mapping
problem, in which any one behaviour can be generated by multiple possible cognitive …

We address the problem of synthesizing multi-view optical illusions: images that change
appearance upon a transformation such as a flip or rotation. We propose a simple zero-shot …

Convolutional neural networks have become the most widely used tool for computer vision
applications like image classification, segmentation, object localization etc. Recent studies …

With the rise of machines to human-level performance in complex recognition tasks, a
growing amount of work is directed toward comparing information processing in humans …

The study of visual illusions has proven to be a very useful approach in vision science. In
this work we start by showing that, while convolutional neural networks (CNNs) trained for …

Abstract Vision-Language Models (VLMs) are trained on vast amounts of data captured by
humans emulating our understanding of the world. However, known as visual illusions …

The question of whether artificial beings or machines could become self-aware or
consciousness has been a philosophical question for centuries. The main problem is that …

This work describes neural network surrogate models for calculating the effective
mechanical properties of a periodic composites. The models achieve good accuracy even …

The responses of visual neurons, as well as visual perception phenomena in general, are
highly nonlinear functions of the visual input, while most vision models are grounded on the …