A rotor-based layer built from bivector exponentials approximates LLM attention projections with O(log^2 d) parameters and competitive downstream performance.
Introduction to Clifford's Geometric Algebra
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abstract
Geometric algebra was initiated by W.K. Clifford over 130 years ago. It unifies all branches of physics, and has found rich applications in robotics, signal processing, ray tracing, virtual reality, computer vision, vector field processing, tracking, geographic information systems and neural computing. This tutorial explains the basics of geometric algebra, with concrete examples of the plane, of 3D space, of spacetime, and the popular conformal model. Geometric algebras are ideal to represent geometric transformations in the general framework of Clifford groups (also called versor or Lipschitz groups). Geometric (algebra based) calculus allows, e.g., to optimize learning algorithms of Clifford neurons, etc. Keywords: Hypercomplex algebra, hypercomplex analysis, geometry, science, engineering.
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Composing Linear Layers from Irreducibles
A rotor-based layer built from bivector exponentials approximates LLM attention projections with O(log^2 d) parameters and competitive downstream performance.