2025
PETRA: Parallel End-to-end Training with Reversible Architectures
Stephane Rivaud, Louis Fournier, Thomas Pumir, Eugene Belilovsky, Michael Eickenberg, Edouard Oyallon
ICLR 2025spotlight
Reversible architectures have been shown to be capable of performing on par with their non-reversible architectures, being applied in deep learning for memory savings and generative modeling. In this work, we show how reversible architectures can solve challenges in parallelizing deep model training…