top | item 41164026 (no title) zygy | 1 year ago Naive question: what's the intuition for how this is different from increasing the number of learnable parameters on a regular MLP? discuss order hn newest slashdave|1 year ago Orthogonality ensures that each weight has its own, individual importance. In a regular MLP, the weights are naturally correlated.
slashdave|1 year ago Orthogonality ensures that each weight has its own, individual importance. In a regular MLP, the weights are naturally correlated.
slashdave|1 year ago