In the rapidly evolving landscape of genomics, deep learning has emerged as a useful tool
for tackling complex computational challenges. This review focuses on the transformative …

Modern machine learning has subverted and bypassed the theoretical framework of
Chomsky's generative approach to linguistics, including its core claims to particular insights …

The utility of machine learning in understanding the motor system is promising a revolution
in how to collect, measure, and analyze data. The field of movement science already …

The brain is the perfect place to look for inspiration to develop more efficient neural
networks. The inner workings of our synapses and neurons provide a glimpse at what the …

We introduce Brain-Inspired Modular Training (BIMT), a method for making neural networks
more modular and interpretable. Inspired by brains, BIMT embeds neurons in a geometric …

The visual system of mammals is comprised of parallel, hierarchical specialized pathways.
Different pathways are specialized in so far as they use representations that are more …

Recognition of objects from sensory stimuli is essential for survival. To that end, sensory
networks in the brain must form object representations invariant to stimulus changes, such …

Materials and machines are often designed with particular goals in mind, so that they exhibit
desired responses to given forces or constraints. Here we explore an alternative approach …

Humans and other animals demonstrate a remarkable ability to generalize knowledge
across distinct contexts and objects during natural behavior. We posit that this ability to …

Machine learning-based malware analysis approaches are widely researched and
deployed in critical infrastructures for detecting and classifying evasive and growing …