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📚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#moe#gating network+12
📚TheoryIntermediate

Key-Value Memory Systems

Key-Value memory systems store information as pairs where keys are used to look up values by similarity rather than exact match.

#key-value memory
Intermediate
Advanced
Group:
Attention & Transformer Theory
#attention
#scaled dot-product
+12
📚TheoryIntermediate

Self-Attention as Graph Neural Network

Self-attention can be viewed as message passing on a fully connected graph where each token (node) sends a weighted message to every other token.

#self-attention#graph neural network#message passing+11
📚TheoryIntermediate

Multi-Head Attention

Multi-Head Attention runs several attention mechanisms in parallel so each head can focus on different relationships in the data.

#multi-head attention#scaled dot-product attention#transformer+12
📚TheoryIntermediate

Scaled Dot-Product Attention

Scaled dot-product attention scores how much each value V should contribute to a query by taking dot products with keys K, scaling by \(\sqrt{d_k}\), applying softmax, and forming a weighted sum.

#scaled dot-product attention#softmax#transformer+10