Random-perturbation, forward-pass-only training is demonstrated on simulated and physical reservoir networks, but it underperforms backpropagation on the transformer test and shows no verified pre-reservoir learning.
Q&A: UW researcher discusses just how much energy ChatGPT uses — washington.edu,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
cs.LG 1years
2025 1verdicts
REJECT 1roles
background 1polarities
unclear 1representative citing papers
citing papers explorer
-
Perturbative Gradient Training: A novel training paradigm for bridging the gap between deep neural networks and physical reservoir computing
Random-perturbation, forward-pass-only training is demonstrated on simulated and physical reservoir networks, but it underperforms backpropagation on the transformer test and shows no verified pre-reservoir learning.