Energy-Efficient Deep Learning Without Backpropagation: A Rigorous Hardware-Validated Benchmarking Study of Forward-Only Algorithms
Faster convergence is the remaining target for an end-to-end gain in forward-only deep learning, and a pre-registered ablation identifies gradient detachment, not MF's auxiliary losses, as the dominant factor tested.