Rishabh Raj

This paper introduces a biologically realistic local learning rule that enables recurrent networks to achieve invariant object representation and classification without error backpropagation.

The paper proposes a computational framework based on maximal dependence capturing to generate invariant object representations, demonstrating its effectiveness in symbol and face recognition under noisy conditions.