What is a G-GLN Neuron?
A G-GLN Neuron is a type of neuron used in the G-GLN architecture. The G-GLN architecture uses a weighted product of Gaussians to give further representational power to a neural network. The G-GLN neuron is the key component that enables the addition of contextual gating, allowing the selection of a weight vector from a table of weight vectors that is appropriate for a given example.
How does a G-GLN Neuron work?
The G-GLN neuron is parameterized by a weight matrix th
A Gated Linear Network, also known as GLN, is a type of neural architecture that works differently from contemporary neural networks. The credit assignment mechanism in GLN is local and distributed, meaning each neuron predicts the target directly without learning feature representations.
Structure of GLNs
GLNs are feedforward networks comprising multiple layers of gated geometric mixing neurons. Each neuron in a particular layer produces a gated geometric mixture of predictions from the prev
G-GLN, which stands for Gaussian Gated Linear Network, is a deep neural network that extends the GLN family of deep neural networks. The GLN neuron is reformulated as a gated product of Gaussians. A Gaussian Gated Linear Network (G-GLN) is a feed-forward network of data-dependent distributions, where every neuron in the G-GLN directly predicts the target distribution.
What is G-GLN?
Gaussian Gated Linear Network, or G-GLN, is a deep neural network that extends the GLN family of neural network