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∑MathIntermediate

Group Theory for Neural Networks

Group theory gives a precise language for symmetries, and neural networks can exploit these symmetries to learn faster and generalize better.

#group theory#neural networks#equivariance+12
📚TheoryIntermediate

Mixture of Experts (MoE)

A Mixture of Experts (MoE) routes each input to a small subset of specialized models called experts, enabling conditional computation.

#mixture of experts
Advanced
Filtering by:
#neural networks
#moe
#gating network
+12
📚TheoryIntermediate

Dropout

Dropout randomly turns off (zeros) some neurons during training to prevent the network from memorizing the training data.

#dropout#inverted dropout#bernoulli mask+12
📚TheoryIntermediate

Spectral Normalization

Spectral normalization rescales a weight matrix so its largest singular value (spectral norm) is at most a target value, typically 1.

#spectral normalization#spectral norm#singular value+12
📚TheoryIntermediate

Weight Initialization Strategies

Weight initialization sets the starting values of neural network parameters so signals and gradients neither explode nor vanish as they pass through layers.

#xavier#glorot#he+12