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Activation functions in neural networks: Types and examples

In this video, we will see What is Activation Function in Neural network, types of Activation function in Neural Network, why ...
Noozhawk

AI Helps Explain How Covert Attention Works and Uncovers New Neuron Types

Shifting focus on a visual scene without moving our eyes — think driving, or reading a room for the reaction to your joke — is a behavior known as covert ...
Science Daily

Synchronization in neural nets: Mathematical insight into neuron readout drives significant improvements in prediction accuracy

Researchers applied the mathematical theory of synchronization to clarify how recurrent neural networks (RNNs) generate predictions, revealing a certain map, based on the generalized synchronization, ...
EurekAlert!

Multiplexed neuron sets make smaller optical neural networks possible

(A) A traditional fully connected neural network. The layers are connected by black lines corresponding to weights. The neurons separately realize the summation and nonlinear activation functions ...
Nanowerk

Artificial neural network hardware based on stacked neuron-synapse-neuron structural blocks

In order for large-scale artificial neural network hardware to become practical in the future, it is essential to integrate artificial neuron and synaptic devices, and it is necessary to reduce mass ...
EurekAlert!

Novel neuron-like ferroelectric bioelectronics enable seamless integration and adaptive communication with neuronal networks

Implantable bioelectronics are vital to neuroscience, neurological therapies, and brain-machine interfaces. They serve as indispensable interfaces that enable the communication between biological ...
eLife

Human EEG and artificial neural networks reveal disentangled representations and processing timelines of object real-world size and depth in natural images

Neural and computational evidence reveals that real-world size is a temporally late, semantically grounded, and hierarchically stable dimension of object representation in both human brains and ...

Interpretable neural networks help reveal the nature of dark matter

A research team from the Xinjiang Astronomical Observatory (XAO) of the Chinese Academy of Sciences has developed an interpretable artificial intelligence (AI) framework named Convolutional Kolmogorov ...