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
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 48 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 25 18 0 04 Nov 2021
Fourier Neural Networks for Function Approximation R. Subhash K. Yaswanth 20 1 0 21 Oct 2021
Meta Internal Learning Raphael Bensadoun Shir Gur Tomer Galanti Lior Wolf GAN 31 8 0 06 Oct 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 29 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 24 194 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 174 246 0 01 May 2021
Deep limits and cut-off phenomena for neural networks B. Avelin A. Karlsson AI4CE 32 2 0 21 Apr 2021
Elvet -- a neural network-based differential equation and variational problem solver Jack Y. Araz J. C. Criado M. Spannowsky 21 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 13 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 24 17 0 11 Mar 2021
Optimal Approximation Rate of ReLU Networks in terms of Width and Depth Zuowei Shen Haizhao Yang Shijun Zhang 101 115 0 28 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 32 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
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 15 11 0 15 Oct 2020
Prediction intervals for Deep Neural Networks Tullio Mancini Hector F. Calvo-Pardo Jose Olmo UQCV OOD 23 4 0 08 Oct 2020
The Traveling Observer Model: Multi-task Learning Through Spatial Variable Embeddings Elliot Meyerson Risto Miikkulainen 16 12 0 05 Oct 2020
Review: Deep Learning in Electron Microscopy Jeffrey M. Ede 34 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 81 1 0 29 Jul 2020
Multi-Task Learning for Multi-Dimensional Regression: Application to Luminescence Sensing Umberto Umberto Michelucci F. Venturini AI4CE 13 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
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 30 121 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 11 26 0 30 May 2020
How hard is to distinguish graphs with graph neural networks? Andreas Loukas GNN 25 6 0 13 May 2020
Active Training of Physics-Informed Neural Networks to Aggregate and Interpolate Parametric Solutions to the Navier-Stokes Equations Christopher J. Arthurs A. King PINN 37 51 0 02 May 2020
On Deep Instrumental Variables Estimate Ruiqi Liu Zuofeng Shang Guang Cheng 24 25 0 30 Apr 2020
It's Not What Machines Can Learn, It's What We Cannot Teach Gal Yehuda Moshe Gabel Assaf Schuster FaML 14 37 0 21 Feb 2020
A closer look at the approximation capabilities of neural networks Kai Fong Ernest Chong 13 16 0 16 Feb 2020
Invariant Risk Minimization Games Kartik Ahuja Karthikeyan Shanmugam Kush R. Varshney Amit Dhurandhar OOD 21 244 0 11 Feb 2020
Deep Network Approximation for Smooth Functions Jianfeng Lu Zuowei Shen Haizhao Yang Shijun Zhang 67 247 0 09 Jan 2020
Sparse Weight Activation Training Md Aamir Raihan Tor M. Aamodt 34 73 0 07 Jan 2020
Deep Learning via Dynamical Systems: An Approximation Perspective Qianxiao Li Ting Lin Zuowei Shen AI4TS AI4CE 16 107 0 22 Dec 2019
Are Transformers universal approximators of sequence-to-sequence functions? Chulhee Yun Srinadh Bhojanapalli A. S. Rawat Sashank J. Reddi Sanjiv Kumar 6 335 0 20 Dec 2019
Deep Learning-based Limited Feedback Designs for MIMO Systems Jeonghyeon Jang Hoon Lee S. Hwang Haibao Ren Inkyu Lee AI4CE 14 32 0 19 Dec 2019
Analysis of Deep Neural Networks with Quasi-optimal polynomial approximation rates Joseph Daws Clayton Webster 30 8 0 04 Dec 2019