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 …

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 …

Emerging interests have been brought to recognize previously unseen objects given very
few training examples, known as few-shot object detection (FSOD). Recent researches …

Deep neural networks (DNNs) have had extraordinary successes in classifying
photographic images of objects and are often described as the best models of biological …

Deep neural networks (DNNs) are machine learning algorithms that have revolutionized
computer vision due to their remarkable successes in tasks like object classification and …

Conceptual abstraction and analogy‐making are key abilities underlying humans' abilities to
learn, reason, and robustly adapt their knowledge to new domains. Despite a long history of …

Interpretable methods based on prototypical patches recognize various components in an
image in order to explain their reasoning to humans. However, existing prototype-based …

Biological and artificial information processing systems form representations of the world
that they can use to categorize, reason, plan, navigate, and make decisions. To what extent …

An important component for generalization in machine learning is to uncover underlying
latent factors of variation as well as the mechanism through which each factor acts in the …

Reflectance, lighting and geometry combine in complex ways to create images. How do we
disentangle these to perceive individual properties, such as surface glossiness? We suggest …