Beyond BatchNorm: Towards a Unified Understanding of Normalization in Deep Learning

10 June 2021

Papers citing "Beyond BatchNorm: Towards a Unified Understanding of Normalization in Deep Learning"

7 / 7 papers shown

Title
ABCAS: Adaptive Bound Control of spectral norm as Automatic Stabilizer Shota Hirose Shiori Maki Naoki Wada Heming Sun J. Katto 35 0 0 12 Nov 2022
Understanding the Generalization Benefit of Normalization Layers: Sharpness Reduction Kaifeng Lyu Zhiyuan Li Sanjeev Arora FAtt 45 70 0 14 Jun 2022
On the Pitfalls of Batch Normalization for End-to-End Video Learning: A Study on Surgical Workflow Analysis Dominik Rivoir Isabel Funke Stefanie Speidel 24 17 0 15 Mar 2022
A Field Guide to Federated Optimization Jianyu Wang Zachary B. Charles Zheng Xu Gauri Joshi H. B. McMahan ... Mi Zhang Tong Zhang Chunxiang Zheng Chen Zhu Wennan Zhu FedML 187 412 0 14 Jul 2021
Is Batch Norm unique? An empirical investigation and prescription to emulate the best properties of common normalizers without batch dependence Vinay Rao Jascha Narain Sohl-Dickstein BDL 40 4 0 21 Oct 2020
BYOL works even without batch statistics Pierre Harvey Richemond Jean-Bastien Grill Florent Altché Corentin Tallec Florian Strub ... Samuel L. Smith Soham De Razvan Pascanu Bilal Piot Michal Valko SSL 250 114 0 20 Oct 2020
TaskNorm: Rethinking Batch Normalization for Meta-Learning J. Bronskill Jonathan Gordon James Requeima Sebastian Nowozin Richard Turner 71 89 0 06 Mar 2020