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Deep Learning without Shortcuts: Shaping the Kernel with Tailored
  Rectifiers

Deep Learning without Shortcuts: Shaping the Kernel with Tailored Rectifiers

15 March 2022
Guodong Zhang
Aleksandar Botev
James Martens
    OffRL
ArXivPDFHTML

Papers citing "Deep Learning without Shortcuts: Shaping the Kernel with Tailored Rectifiers"

14 / 14 papers shown
Title
Normalization and effective learning rates in reinforcement learning
Normalization and effective learning rates in reinforcement learning
Clare Lyle
Zeyu Zheng
Khimya Khetarpal
James Martens
H. V. Hasselt
Razvan Pascanu
Will Dabney
19
7
0
01 Jul 2024
Understanding and Minimising Outlier Features in Neural Network Training
Understanding and Minimising Outlier Features in Neural Network Training
Bobby He
Lorenzo Noci
Daniele Paliotta
Imanol Schlag
Thomas Hofmann
39
3
0
29 May 2024
Understanding plasticity in neural networks
Understanding plasticity in neural networks
Clare Lyle
Zeyu Zheng
Evgenii Nikishin
Bernardo Avila-Pires
Razvan Pascanu
Will Dabney
AI4CE
35
97
0
02 Mar 2023
Width and Depth Limits Commute in Residual Networks
Width and Depth Limits Commute in Residual Networks
Soufiane Hayou
Greg Yang
42
14
0
01 Feb 2023
RepMode: Learning to Re-parameterize Diverse Experts for Subcellular
  Structure Prediction
RepMode: Learning to Re-parameterize Diverse Experts for Subcellular Structure Prediction
Donghao Zhou
Chunbin Gu
Junde Xu
Furui Liu
Qiong Wang
Guangyong Chen
Pheng-Ann Heng
MoE
13
4
0
20 Dec 2022
On skip connections and normalisation layers in deep optimisation
On skip connections and normalisation layers in deep optimisation
L. MacDonald
Jack Valmadre
Hemanth Saratchandran
Simon Lucey
ODL
19
1
0
10 Oct 2022
AutoInit: Automatic Initialization via Jacobian Tuning
AutoInit: Automatic Initialization via Jacobian Tuning
Tianyu He
Darshil Doshi
Andrey Gromov
14
4
0
27 Jun 2022
Gaussian Pre-Activations in Neural Networks: Myth or Reality?
Gaussian Pre-Activations in Neural Networks: Myth or Reality?
Pierre Wolinski
Julyan Arbel
AI4CE
73
8
0
24 May 2022
Rapid training of deep neural networks without skip connections or
  normalization layers using Deep Kernel Shaping
Rapid training of deep neural networks without skip connections or normalization layers using Deep Kernel Shaping
James Martens
Andy Ballard
Guillaume Desjardins
G. Swirszcz
Valentin Dalibard
Jascha Narain Sohl-Dickstein
S. Schoenholz
88
43
0
05 Oct 2021
High-Performance Large-Scale Image Recognition Without Normalization
High-Performance Large-Scale Image Recognition Without Normalization
Andrew Brock
Soham De
Samuel L. Smith
Karen Simonyan
VLM
223
512
0
11 Feb 2021
RepVGG: Making VGG-style ConvNets Great Again
RepVGG: Making VGG-style ConvNets Great Again
Xiaohan Ding
Xinming Zhang
Ningning Ma
Jungong Han
Guiguang Ding
Jian Sun
136
1,548
0
11 Jan 2021
Stable ResNet
Stable ResNet
Soufiane Hayou
Eugenio Clerico
Bo He
George Deligiannidis
Arnaud Doucet
Judith Rousseau
ODL
SSeg
46
51
0
24 Oct 2020
Deep Networks and the Multiple Manifold Problem
Deep Networks and the Multiple Manifold Problem
Sam Buchanan
D. Gilboa
John N. Wright
166
39
0
25 Aug 2020
Dynamical Isometry and a Mean Field Theory of CNNs: How to Train
  10,000-Layer Vanilla Convolutional Neural Networks
Dynamical Isometry and a Mean Field Theory of CNNs: How to Train 10,000-Layer Vanilla Convolutional Neural Networks
Lechao Xiao
Yasaman Bahri
Jascha Narain Sohl-Dickstein
S. Schoenholz
Jeffrey Pennington
233
348
0
14 Jun 2018
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