Understanding Deep Neural Networks with Rectified Linear Units

4 November 2016

Papers citing "Understanding Deep Neural Networks with Rectified Linear Units"

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Title
ReLU Deep Neural Networks from the Hierarchical Basis Perspective Juncai He Lin Li Jinchao Xu AI4CE 28 30 0 10 May 2021
What Kinds of Functions do Deep Neural Networks Learn? Insights from Variational Spline Theory Rahul Parhi Robert D. Nowak MLT 38 70 0 07 May 2021
Sharp bounds for the number of regions of maxout networks and vertices of Minkowski sums Guido Montúfar Yue Ren Leon Zhang 20 39 0 16 Apr 2021
Fast Jacobian-Vector Product for Deep Networks Randall Balestriero Richard Baraniuk 31 4 0 01 Apr 2021
Pareto GAN: Extending the Representational Power of GANs to Heavy-Tailed Distributions Todd P. Huster Jérémy E. Cohen Zinan Lin Kevin S. Chan Charles A. Kamhoua Nandi O. Leslie C. Chiang Vyas Sekar GAN 46 26 0 22 Jan 2021
Know Your Limits: Uncertainty Estimation with ReLU Classifiers Fails at Reliable OOD Detection Dennis Ulmer Giovanni Cina OODD 35 31 0 09 Dec 2020
Dissipative Deep Neural Dynamical Systems Ján Drgoňa Soumya Vasisht Aaron Tuor D. Vrabie 21 7 0 26 Nov 2020
Deep neural network for solving differential equations motivated by Legendre-Galerkin approximation Bryce Chudomelka Youngjoon Hong Hyunwoo J. Kim Jinyoung Park 27 7 0 24 Oct 2020
On the Number of Linear Functions Composing Deep Neural Network: Towards a Refined Definition of Neural Networks Complexity Yuuki Takai Akiyoshi Sannai Matthieu Cordonnier 77 4 0 23 Oct 2020
Neural Star Domain as Primitive Representation Yuki Kawana Yusuke Mukuta Tatsuya Harada 3DV 11 25 0 21 Oct 2020
Learning to Embed Categorical Features without Embedding Tables for Recommendation Wang-Cheng Kang D. Cheng Tiansheng Yao Xinyang Yi Ting-Li Chen Lichan Hong Ed H. Chi LMTD CML DML 50 68 0 21 Oct 2020
Effects of the Nonlinearity in Activation Functions on the Performance of Deep Learning Models N. Kulathunga N. R. Ranasinghe D. Vrinceanu Zackary Kinsman Lei Huang Yunjiao Wang 6 4 0 14 Oct 2020
Expressivity of Deep Neural Networks Ingo Gühring Mones Raslan Gitta Kutyniok 16 51 0 09 Jul 2020
ConFoc: Content-Focus Protection Against Trojan Attacks on Neural Networks Miguel Villarreal-Vasquez B. Bhargava AAML 17 38 0 01 Jul 2020
Interpreting and Disentangling Feature Components of Various Complexity from DNNs Jie Ren Mingjie Li Zexu Liu Quanshi Zhang CoGe 19 18 0 29 Jun 2020
Universal Function Approximation on Graphs Rickard Brüel-Gabrielsson 32 6 0 14 Mar 2020
Neural Networks are Convex Regularizers: Exact Polynomial-time Convex Optimization Formulations for Two-layer Networks Mert Pilanci Tolga Ergen 26 116 0 24 Feb 2020
Being Bayesian, Even Just a Bit, Fixes Overconfidence in ReLU Networks Agustinus Kristiadi Matthias Hein Philipp Hennig BDL UQCV 33 277 0 24 Feb 2020
On the Decision Boundaries of Neural Networks: A Tropical Geometry Perspective Motasem Alfarra Adel Bibi Hasan Hammoud M. Gaafar Guohao Li 16 26 0 20 Feb 2020
A closer look at the approximation capabilities of neural networks Kai Fong Ernest Chong 18 16 0 16 Feb 2020
On Approximation Capabilities of ReLU Activation and Softmax Output Layer in Neural Networks Behnam Asadi Hui Jiang 10 20 0 10 Feb 2020
Empirical Studies on the Properties of Linear Regions in Deep Neural Networks Xiao Zhang Dongrui Wu 21 38 0 04 Jan 2020
Lossless Compression of Deep Neural Networks Thiago Serra Abhinav Kumar Srikumar Ramalingam 24 56 0 01 Jan 2020
Almost Uniform Sampling From Neural Networks Changlong Wu N. Santhanam 20 0 0 10 Dec 2019
Variational Physics-Informed Neural Networks For Solving Partial Differential Equations E. Kharazmi Z. Zhang George Karniadakis 24 236 0 27 Nov 2019
Deep least-squares methods: an unsupervised learning-based numerical method for solving elliptic PDEs Z. Cai Jingshuang Chen Min Liu Xinyu Liu 10 88 0 05 Nov 2019
Large Scale Model Predictive Control with Neural Networks and Primal Active Sets Steven W. Chen Tianyu Wang Nikolay Atanasov Vijay Kumar M. Morari 17 86 0 23 Oct 2019
Optimal Function Approximation with Relu Neural Networks Bo Liu Yi Liang 25 33 0 09 Sep 2019
Padé Activation Units: End-to-end Learning of Flexible Activation Functions in Deep Networks Alejandro Molina P. Schramowski Kristian Kersting ODL 23 77 0 15 Jul 2019
Controlling Neural Level Sets Matan Atzmon Niv Haim Lior Yariv Ofer Israelov Haggai Maron Y. Lipman AI4CE 22 118 0 28 May 2019
Universal Approximation with Deep Narrow Networks Patrick Kidger Terry Lyons 40 327 0 21 May 2019
DSTP-RNN: a dual-stage two-phase attention-based recurrent neural networks for long-term and multivariate time series prediction Yeqi Liu Chuanyang Gong Ling Yang Yingyi Chen AI4TS 19 305 0 16 Apr 2019
Deep Representation with ReLU Neural Networks Andreas Heinecke W. Hwang 39 0 0 29 Mar 2019
Scaling up the randomized gradient-free adversarial attack reveals overestimation of robustness using established attacks Francesco Croce Jonas Rauber Matthias Hein AAML 20 30 0 27 Mar 2019
A lattice-based approach to the expressivity of deep ReLU neural networks V. Corlay J. Boutros P. Ciblat L. Brunel 11 4 0 28 Feb 2019
$Error bounds for approximations with deep ReLU neural networks in $W^{s,p}$ norms$ Error bounds for approximations with deep ReLU neural networks in $W^{s,p}$ norms Ingo Gühring Gitta Kutyniok P. Petersen 20 199 0 21 Feb 2019
A Constructive Approach for One-Shot Training of Neural Networks Using Hypercube-Based Topological Coverings W. B. Daniel Enoch Yeung 23 2 0 09 Jan 2019
Why ReLU networks yield high-confidence predictions far away from the training data and how to mitigate the problem Matthias Hein Maksym Andriushchenko Julian Bitterwolf OODD 46 552 0 13 Dec 2018
A randomized gradient-free attack on ReLU networks Francesco Croce Matthias Hein AAML 37 21 0 28 Nov 2018
Empirical Bounds on Linear Regions of Deep Rectifier Networks Thiago Serra Srikumar Ramalingam 8 42 0 08 Oct 2018
Understanding Weight Normalized Deep Neural Networks with Rectified Linear Units Yixi Xu Tianlin Li MQ 31 12 0 03 Oct 2018
On the Implicit Bias of Dropout Poorya Mianjy R. Arora René Vidal 27 66 0 26 Jun 2018
On the Spectral Bias of Neural Networks Nasim Rahaman A. Baratin Devansh Arpit Felix Dräxler Min-Bin Lin Fred Hamprecht Yoshua Bengio Aaron Courville 57 1,394 0 22 Jun 2018
Tropical Geometry of Deep Neural Networks Liwen Zhang Gregory Naitzat Lek-Heng Lim 32 137 0 18 May 2018
Mad Max: Affine Spline Insights into Deep Learning Randall Balestriero Richard Baraniuk AI4CE 31 78 0 17 May 2018
A representer theorem for deep neural networks M. Unser 35 98 0 26 Feb 2018
Limits on representing Boolean functions by linear combinations of simple functions: thresholds, ReLUs, and low-degree polynomials Richard Ryan Williams 30 27 0 26 Feb 2018
Script Identification in Natural Scene Image and Video Frame using Attention based Convolutional-LSTM Network A. Bhunia Aishik Konwer A. Bhunia A. Bhowmick P. Roy Umapada Pal 19 124 0 01 Jan 2018
Reliably Learning the ReLU in Polynomial Time Surbhi Goel Varun Kanade Adam R. Klivans J. Thaler 19 124 0 30 Nov 2016
Benefits of depth in neural networks Matus Telgarsky 151 602 0 14 Feb 2016