The Expressive Power of Neural Networks: A View from the Width

8 September 2017

Papers citing "The Expressive Power of Neural Networks: A View from the Width"

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Title
Completely Quantum Neural Networks Steve Abel J. C. Criado M. Spannowsky 25 25 0 23 Feb 2022
Training Thinner and Deeper Neural Networks: Jumpstart Regularization Carles Roger Riera Molina Camilo Rey Thiago Serra Eloi Puertas O. Pujol 27 4 0 30 Jan 2022
Early Detection of Network Attacks Using Deep Learning Tanwir Ahmad D. Truscan Juri Vain Ivan Porres AAML 19 17 0 27 Jan 2022
GPEX, A Framework For Interpreting Artificial Neural Networks Amir Akbarnejad G. Bigras Nilanjan Ray 47 4 0 18 Dec 2021
Learning High-Dimensional Parametric Maps via Reduced Basis Adaptive Residual Networks Thomas O'Leary-Roseberry Xiaosong Du A. Chaudhuri J. Martins Karen E. Willcox Omar Ghattas 30 22 0 14 Dec 2021
NN-LUT: Neural Approximation of Non-Linear Operations for Efficient Transformer Inference Joonsang Yu Junki Park Seongmin Park Minsoo Kim Sihwa Lee Dong Hyun Lee Jungwook Choi 35 50 0 03 Dec 2021
Reconstructing Nonlinear Dynamical Systems from Multi-Modal Time Series Daniel Kramer P. Bommer Carlo Tombolini G. Koppe Daniel Durstewitz BDL AI4TS AI4CE 27 19 0 04 Nov 2021
Quantifying Epistemic Uncertainty in Deep Learning Ziyi Huang H. Lam Haofeng Zhang UQCV BDL UD PER 24 12 0 23 Oct 2021
Fourier Neural Networks for Function Approximation R. Subhash K. Yaswanth 28 1 0 21 Oct 2021
Meta Internal Learning Raphael Bensadoun Shir Gur Tomer Galanti Lior Wolf GAN 31 8 0 06 Oct 2021
Arbitrary-Depth Universal Approximation Theorems for Operator Neural Networks Annan Yu Chloe Becquey Diana Halikias Matthew Esmaili Mallory Alex Townsend 59 8 0 23 Sep 2021
Robust Nonparametric Regression with Deep Neural Networks Guohao Shen Yuling Jiao Yuanyuan Lin Jian Huang OOD 33 13 0 21 Jul 2021
The Limitations of Large Width in Neural Networks: A Deep Gaussian Process Perspective Geoff Pleiss John P. Cunningham 28 24 0 11 Jun 2021
Relational Reasoning Networks G. Marra Michelangelo Diligenti Francesco Giannini NAI 32 4 0 01 Jun 2021
ReLU Deep Neural Networks from the Hierarchical Basis Perspective Juncai He Lin Li Jinchao Xu AI4CE 28 30 0 10 May 2021
A Geometric Analysis of Neural Collapse with Unconstrained Features Zhihui Zhu Tianyu Ding Jinxin Zhou Xiao Li Chong You Jeremias Sulam Qing Qu 40 196 0 06 May 2021
SpookyNet: Learning Force Fields with Electronic Degrees of Freedom and Nonlocal Effects Oliver T. Unke Stefan Chmiela M. Gastegger Kristof T. Schütt H. E. Sauceda K. Müller 177 248 0 01 May 2021
Deep limits and cut-off phenomena for neural networks B. Avelin A. Karlsson AI4CE 38 2 0 21 Apr 2021
Causal Reasoning in Simulation for Structure and Transfer Learning of Robot Manipulation Policies Timothy E. Lee Jialiang Zhao A. Sawhney Siddharth Girdhar Oliver Kroemer CML 21 32 0 31 Mar 2021
Elvet -- a neural network-based differential equation and variational problem solver Jack Y. Araz J. C. Criado M. Spannowsky 26 13 0 26 Mar 2021
JFB: Jacobian-Free Backpropagation for Implicit Networks Samy Wu Fung Howard Heaton Qiuwei Li Daniel McKenzie Stanley Osher W. Yin FedML 35 84 0 23 Mar 2021
Deep KKL: Data-driven Output Prediction for Non-Linear Systems Steeven Janny V. Andrieu Madiha Nadri Wolf Christian Wolf AI4TS 22 13 0 23 Mar 2021
$Function approximation by deep neural networks with parameters $\{0,\pm \frac{1}{2}, \pm 1, 2\}$$ Function approximation by deep neural networks with parameters $\{0,\pm \frac{1}{2}, \pm 1, 2\}$ A. Beknazaryan 18 5 0 15 Mar 2021
$Non-Asymptotic Performance Guarantees for Neural Estimation of $\mathsf{f}$-Divergences$ Non-Asymptotic Performance Guarantees for Neural Estimation of $\mathsf{f}$ -Divergences Sreejith Sreekumar Zhengxin Zhang Ziv Goldfeld FedML 32 17 0 11 Mar 2021
Optimal Approximation Rate of ReLU Networks in terms of Width and Depth Zuowei Shen Haizhao Yang Shijun Zhang 103 115 0 28 Feb 2021
Training Larger Networks for Deep Reinforcement Learning Keita Ota Devesh K. Jha Asako Kanezaki OffRL 25 39 0 16 Feb 2021
Scaling Up Bayesian Uncertainty Quantification for Inverse Problems using Deep Neural Networks Shiwei Lan Shuyi Li Babak Shahbaba UQCV BDL 25 16 0 11 Jan 2021
Advances in Electron Microscopy with Deep Learning Jeffrey M. Ede 37 2 0 04 Jan 2021
Convex Potential Flows: Universal Probability Distributions with Optimal Transport and Convex Optimization Chin-Wei Huang Ricky T. Q. Chen Christos Tsirigotis Aaron Courville OT 119 95 0 10 Dec 2020
The universal approximation theorem for complex-valued neural networks F. Voigtlaender 27 62 0 06 Dec 2020
On the application of Physically-Guided Neural Networks with Internal Variables to Continuum Problems J. Ayensa-Jiménez M. H. Doweidar J. A. Sanz-Herrera Manuel Doblaré 24 1 0 23 Nov 2020
Rethinking the Value of Transformer Components Wenxuan Wang Zhaopeng Tu 11 38 0 07 Nov 2020
A Perspective on Machine Learning Methods in Turbulence Modelling Andrea Beck Marius Kurz AI4CE 47 101 0 23 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
Towards Reflectivity profile inversion through Artificial Neural Networks J. M. Carmona Loaiza Zamaan Raza 29 11 0 15 Oct 2020
Machine Learning Force Fields Oliver T. Unke Stefan Chmiela H. E. Sauceda M. Gastegger I. Poltavsky Kristof T. Schütt A. Tkatchenko K. Müller AI4CE 34 888 0 14 Oct 2020
Prediction intervals for Deep Neural Networks Tullio Mancini Hector F. Calvo-Pardo Jose Olmo UQCV OOD 25 4 0 08 Oct 2020
The Traveling Observer Model: Multi-task Learning Through Spatial Variable Embeddings Elliot Meyerson Risto Miikkulainen 21 12 0 05 Oct 2020
Review: Deep Learning in Electron Microscopy Jeffrey M. Ede 36 79 0 17 Sep 2020
Malicious Network Traffic Detection via Deep Learning: An Information Theoretic View Erick Galinkin AAML 15 0 0 16 Sep 2020
Unnormalized Variational Bayes Saeed Saremi BDL 86 1 0 29 Jul 2020
Multi-Task Learning for Multi-Dimensional Regression: Application to Luminescence Sensing Umberto Umberto Michelucci F. Venturini AI4CE 21 19 0 27 Jul 2020
Learnable Descent Algorithm for Nonsmooth Nonconvex Image Reconstruction Yunmei Chen Hongcheng Liu X. Ye Qingchao Zhang 56 23 0 22 Jul 2020
Expressivity of Deep Neural Networks Ingo Gühring Mones Raslan Gitta Kutyniok 16 51 0 09 Jul 2020
Predicting First Passage Percolation Shapes Using Neural Networks Sebastian Rosengren AI4CE 14 0 0 24 Jun 2020
The Depth-to-Width Interplay in Self-Attention Yoav Levine Noam Wies Or Sharir Hofit Bata Amnon Shashua 30 45 0 22 Jun 2020
Minimum Width for Universal Approximation Sejun Park Chulhee Yun Jaeho Lee Jinwoo Shin 35 122 0 16 Jun 2020
Scalable Partial Explainability in Neural Networks via Flexible Activation Functions S. Sun Chen Li Zhuangkun Wei Antonios Tsourdos Weisi Guo FAtt 32 2 0 10 Jun 2020
Learning Efficient Representations of Mouse Movements to Predict User Attention Ioannis Arapakis Luis A. Leiva HAI 19 26 0 30 May 2020
How hard is to distinguish graphs with graph neural networks? Andreas Loukas GNN 25 6 0 13 May 2020