Event cameras are bio-inspired sensors that differ from conventional frame cameras: Instead
of capturing images at a fixed rate, they asynchronously measure per-pixel brightness …

In recent years, deep artificial neural networks (including recurrent ones) have won
numerous contests in pattern recognition and machine learning. This historical survey …

Deep neural networks have emerged as a widely used and effective means for tackling
complex, real-world problems. However, a major obstacle in applying them to safety-critical …

The fields of neuroscience and artificial intelligence (AI) have a long and intertwined history.
In more recent times, however, communication and collaboration between the two fields has …

Brains contain networks of interconnected neurons and so knowing the network architecture
is essential for understanding brain function. We therefore mapped the synaptic-resolution …

How is it that thoroughly physical material beings such as ourselves can think, dream, feel,
create and understand ideas, theories and concepts? How does mere matter give rise to all …

Deep-learning (DL) algorithms, which learn the representative and discriminative features in
a hierarchical manner from the data, have recently become a hotspot in the machine …

Given a degraded input image, image restoration aims to recover the missing high-quality
image content. Numerous applications demand effective image restoration, eg …

The anatomy of the mammalian visual system, from the retina to the neocortex, is organized
hierarchically. However, direct observation of cellular-level functional interactions across this …

The success of machine learning algorithms generally depends on data representation, and
we hypothesize that this is because different representations can entangle and hide more or …