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E(n) Equivariant Neural Networks

E(n)-equivariant neural networks are models whose outputs transform predictably when inputs are rotated, translated, or reflected in n-dimensional Euclidean space.

#e(n)-equivariance#euclidean group#so(n) and o(n)+12
∑MathIntermediate

Positional Encoding Mathematics

Sinusoidal positional encoding represents each token’s position using pairs of sine and cosine waves at exponentially spaced frequencies.

#positional encoding
Advanced
Filtering by:
#relative position
#sinusoidal
#transformer
+11
📚TheoryIntermediate

Positional Encoding Theory

Transformers are permutation-invariant by default, so they need positional encodings to understand word order in sequences.

#positional encoding#sinusoidal encoding#transformer+11