Explore 20 powerful activation functions for deep neural networks using Python! From ReLU and ELU to Sigmoid and Cosine, ...

In 1982 physicist John Hopfield translated this theoretical neuroscience concept into the artificial intelligence realm, with the formulation of the Hopfield network. In doing so, not only did he ...

Mapping a new brain network for naming Date: May 13, 2025 Source: NYU Tandon School of Engineering Summary: Researchers identified two brain networks involved in word retrieval -- the cognitive ...

Confused about activation functions in neural networks? This video breaks down what they are, why they matter, and the most common types — including ReLU, Sigmoid, Tanh, and more! # ...

However, few strategies exist for brain-wide mapping of multiple ensembles, including their overlapping population, and none incorporate capabilities for downstream network analysis. Here, we ...

The presented paradox would be a useful conceptual tool to keep on disentangling neural and behavioral underpinnings of awake cognitive mapping and, as a result, a key to obtaining a better ...

With the equivariant neural network suite PiNN introduced here, we are ready for this challenge and anticipating many interesting applications to realistic electrochemical systems coming out soon.

With growing model complexity, mapping spiking neural network (SNN)-based applications to tile-based neuromorphic hardware is becoming increasingly challenging. This is because the synaptic storage ...

Scientists traced connectivity between neurons to identify how the brain communicates with the spinal cord to control motor function.