2 papers
cs.LG2026
Lookahead Drifting Model
Guoqiang Zhang, Kenta Niwa, W. Bastiaan Kleijn
Recently, a new paradigm named \emph{drifting model} has been proposed for mapping distributions, which achieves the SOTA image generation performance over ImageNet via one-step ne…
cs.LG2024
On Exact Bit-level Reversible Transformers Without Changing Architectures
Guoqiang Zhang, J. P. Lewis, W. B. Kleijn
Various reversible deep neural networks (DNN) models have been proposed to reduce memory consumption in the training process. However, almost all existing reversible DNNs either re…