Natural Neural Networks

1 July 2015

Papers citing "Natural Neural Networks"

36 / 36 papers shown

Title
Budgeted Online Continual Learning by Adaptive Layer Freezing and Frequency-based Sampling Minhyuk Seo Hyunseo Koh Jonghyun Choi 31 1 0 19 Oct 2024
The Geometry of Neural Nets' Parameter Spaces Under Reparametrization Agustinus Kristiadi Felix Dangel Philipp Hennig 22 11 0 14 Feb 2023
Random initialisations performing above chance and how to find them Frederik Benzing Simon Schug Robert Meier J. Oswald Yassir Akram Nicolas Zucchet Laurence Aitchison Angelika Steger ODL 17 24 0 15 Sep 2022
What do CNNs Learn in the First Layer and Why? A Linear Systems Perspective Rhea Chowers Yair Weiss 31 2 0 06 Jun 2022
Feedback Gradient Descent: Efficient and Stable Optimization with Orthogonality for DNNs Fanchen Bu D. Chang 17 6 0 12 May 2022
Approximate Nearest Neighbor Search under Neural Similarity Metric for Large-Scale Recommendation Rihan Chen Bin Liu Han Zhu Yao Wang Qi Li ... Q. hua Junliang Jiang Yunlong Xu Hongbo Deng Bo Zheng 23 20 0 14 Feb 2022
Gradient Descent on Neurons and its Link to Approximate Second-Order Optimization Frederik Benzing ODL 35 23 0 28 Jan 2022
Low-Pass Filtering SGD for Recovering Flat Optima in the Deep Learning Optimization Landscape Devansh Bisla Jing Wang A. Choromańska 25 34 0 20 Jan 2022
Powerpropagation: A sparsity inducing weight reparameterisation Jonathan Richard Schwarz Siddhant M. Jayakumar Razvan Pascanu P. Latham Yee Whye Teh 87 54 0 01 Oct 2021
Batch Normalization Preconditioning for Neural Network Training Susanna Lange Kyle E. Helfrich Qiang Ye 22 9 0 02 Aug 2021
TENGraD: Time-Efficient Natural Gradient Descent with Exact Fisher-Block Inversion Saeed Soori Bugra Can Baourun Mu Mert Gurbuzbalaban M. Dehnavi 11 10 0 07 Jun 2021
Shapley Explanation Networks Rui Wang Xiaoqian Wang David I. Inouye TDI FAtt 19 44 0 06 Apr 2021
Information Geometry and Classical Cramér-Rao Type Inequalities Kumar Vijay Mishra M. I. M. Ashok Kumar 16 1 0 02 Apr 2021
EigenGame: PCA as a Nash Equilibrium I. Gemp Brian McWilliams Claire Vernade T. Graepel 13 46 0 01 Oct 2020
Transform Quantization for CNN (Convolutional Neural Network) Compression Sean I. Young Wang Zhe David S. Taubman B. Girod MQ 27 69 0 02 Sep 2020
Whitening and second order optimization both make information in the dataset unusable during training, and can reduce or prevent generalization Neha S. Wadia Daniel Duckworth S. Schoenholz Ethan Dyer Jascha Narain Sohl-Dickstein 19 13 0 17 Aug 2020
Incremental Object Detection via Meta-Learning K. J. Joseph Jathushan Rajasegaran Salman Khan F. Khan V. Balasubramanian ObjD CLL VLM 172 98 0 17 Mar 2020
Out-of-Distribution Generalization via Risk Extrapolation (REx) David M. Krueger Ethan Caballero J. Jacobsen Amy Zhang Jonathan Binas Dinghuai Zhang Rémi Le Priol Aaron Courville OOD 215 901 0 02 Mar 2020
Concept Whitening for Interpretable Image Recognition Zhi Chen Yijie Bei Cynthia Rudin FAtt 14 313 0 05 Feb 2020
Switchable Normalization for Learning-to-Normalize Deep Representation Ping Luo Ruimao Zhang Jiamin Ren Zhanglin Peng Jingyu Li 28 73 0 22 Jul 2019
Natural Option Critic Saket Tiwari Philip S. Thomas 9 22 0 04 Dec 2018
Mode Normalization Lucas Deecke Iain Murray Hakan Bilen OOD 29 33 0 12 Oct 2018
Combining Natural Gradient with Hessian Free Methods for Sequence Training Adnan Haider P. Woodland ODL 9 4 0 03 Oct 2018
Fast Approximate Natural Gradient Descent in a Kronecker-factored Eigenbasis Thomas George César Laurent Xavier Bouthillier Nicolas Ballas Pascal Vincent ODL 13 150 0 11 Jun 2018
Meta-Learning with Hessian-Free Approach in Deep Neural Nets Training Boyu Chen Wenlian Lu Ernest Fokoue 16 1 0 22 May 2018
OLÉ: Orthogonal Low-rank Embedding, A Plug and Play Geometric Loss for Deep Learning José Lezama Qiang Qiu Pablo Musé Guillermo Sapiro 17 78 0 05 Dec 2017
Self-Normalizing Neural Networks G. Klambauer Thomas Unterthiner Andreas Mayr Sepp Hochreiter 11 2,481 0 08 Jun 2017
Sharp Minima Can Generalize For Deep Nets Laurent Dinh Razvan Pascanu Samy Bengio Yoshua Bengio ODL 35 754 0 15 Mar 2017
Relative Natural Gradient for Learning Large Complex Models Ke Sun Frank Nielsen 29 5 0 20 Jun 2016
Parametric Exponential Linear Unit for Deep Convolutional Neural Networks Ludovic Trottier Philippe Giguère B. Chaib-draa 30 199 0 30 May 2016
Normalization Propagation: A Parametric Technique for Removing Internal Covariate Shift in Deep Networks Devansh Arpit Yingbo Zhou Bhargava U. Kota V. Govindaraju 11 126 0 04 Mar 2016
Weight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural Networks Tim Salimans Diederik P. Kingma ODL 40 1,924 0 25 Feb 2016
Learning values across many orders of magnitude H. V. Hasselt A. Guez Matteo Hessel Volodymyr Mnih David Silver 13 169 0 24 Feb 2016
A Kronecker-factored approximate Fisher matrix for convolution layers Roger C. Grosse James Martens ODL 21 257 0 03 Feb 2016
Batch Normalized Recurrent Neural Networks César Laurent Gabriel Pereyra Philemon Brakel Y. Zhang Yoshua Bengio 24 213 0 05 Oct 2015
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift Sergey Ioffe Christian Szegedy OOD 26 43,002 0 11 Feb 2015