Variable Binding for Sparse Distributed Representations: Theory and Applications

Understand

Symbolic reasoning and neural networks are often considered incompatible approaches.

• Connectionist models known as Vector Symbolic Architectures (VSAs) can potentially bridge this gap.
• However, classical VSAs and neural networks are still considered incompatible.
• VSAs encode symbols by dense pseudo-random vectors, where information is distributed throughout the entire neuron population.