Why Deep Neural Networks for Function Approximation?

13 October 2016

Papers citing "Why Deep Neural Networks for Function Approximation?"

50 / 60 papers shown

Title
An extension of linear self-attention for in-context learning Katsuyuki Hagiwara 41 0 0 31 Mar 2025
A Data-Driven Real-Time Optimal Power Flow Algorithm Using Local Feedback Heng Liang Yujin Huang Changhong Zhao 62 0 0 24 Feb 2025
Approximation of Solution Operators for High-dimensional PDEs Nathan Gaby Xiaojing Ye 30 0 0 18 Jan 2024
Deep State-Space Model for Predicting Cryptocurrency Price Shalini Sharma A. Majumdar Émilie Chouzenoux Victor Elvira 28 0 0 21 Nov 2023
Data-Driven Optimal Control of Tethered Space Robot Deployment with Learning Based Koopman Operator Ao Jin Fan Zhang Panfeng Huang 27 3 0 15 Jul 2023
ENN: A Neural Network with DCT Adaptive Activation Functions Marc Martinez-Gost Ana I. Pérez-Neira M. Lagunas AAML 11 6 0 02 Jul 2023
Adaptive Ensemble Q-learning: Minimizing Estimation Bias via Error Feedback Hang Wang Sen Lin Junshan Zhang 21 19 0 20 Jun 2023
A Survey on Solving and Discovering Differential Equations Using Deep Neural Networks Hyeonjung Jung Jung Jayant Gupta B. Jayaprakash Matthew J. Eagon Harish Selvam Carl Molnar W. Northrop Shashi Shekhar AI4CE 35 5 0 26 Apr 2023
Multi-Flow Transmission in Wireless Interference Networks: A Convergent Graph Learning Approach Raz Paul Kobi Cohen Gil Kedar 34 5 0 27 Mar 2023
Lower Bounds on the Depth of Integral ReLU Neural Networks via Lattice Polytopes Christian Haase Christoph Hertrich Georg Loho 34 21 0 24 Feb 2023
Statistical guarantees for sparse deep learning Johannes Lederer 13 11 0 11 Dec 2022
Double Deep Q-Learning in Opponent Modeling Yangtianze Tao J. Doe 26 3 0 24 Nov 2022
Expressibility-Enhancing Strategies for Quantum Neural Networks Y. Liao Junpeng Zhan 26 6 0 23 Nov 2022
Seeking Interpretability and Explainability in Binary Activated Neural Networks Benjamin Leblanc Pascal Germain FAtt 37 1 0 07 Sep 2022
Interpretable Polynomial Neural Ordinary Differential Equations Colby Fronk Linda R. Petzold 27 27 0 09 Aug 2022
Rich Feature Distillation with Feature Affinity Module for Efficient Image Dehazing S. J. Anushri Suresh Nisha J.S. V. Gopi VLM 31 6 0 13 Jul 2022
Why Robust Generalization in Deep Learning is Difficult: Perspective of Expressive Power Binghui Li Jikai Jin Han Zhong J. Hopcroft Liwei Wang OOD 82 27 0 27 May 2022
Sibyl: Adaptive and Extensible Data Placement in Hybrid Storage Systems Using Online Reinforcement Learning Gagandeep Singh Rakesh Nadig Jisung Park Rahul Bera Nastaran Hajinazar D. Novo Juan Gómez Luna S. Stuijk Henk Corporaal O. Mutlu 62 33 0 15 May 2022
$Training Fully Connected Neural Networks is $\exists\mathbb{R}$-Complete$ Training Fully Connected Neural Networks is $\exists\mathbb{R}$ -Complete Daniel Bertschinger Christoph Hertrich Paul Jungeblut Tillmann Miltzow Simon Weber OffRL 59 30 0 04 Apr 2022
De Rham compatible Deep Neural Network FEM M. Longo J. Opschoor Nico Disch Christoph Schwab Jakob Zech 19 8 0 14 Jan 2022
A Simple Single-Scale Vision Transformer for Object Localization and Instance Segmentation Wuyang Chen Xianzhi Du Fan Yang Lucas Beyer Xiaohua Zhai ... Huizhong Chen Jing Li Xiaodan Song Zhangyang Wang Denny Zhou ViT 29 20 0 17 Dec 2021
Fourier Neural Networks for Function Approximation R. Subhash K. Yaswanth 22 1 0 21 Oct 2021
Adaptive Group Lasso Neural Network Models for Functions of Few Variables and Time-Dependent Data L. Ho Nicholas Richardson Giang Tran 18 3 0 24 Aug 2021
Robust Nonparametric Regression with Deep Neural Networks Guohao Shen Yuling Jiao Yuanyuan Lin Jian Huang OOD 33 13 0 21 Jul 2021
Layer Folding: Neural Network Depth Reduction using Activation Linearization Amir Ben Dror Niv Zehngut Avraham Raviv E. Artyomov Ran Vitek R. Jevnisek 29 20 0 17 Jun 2021
Size and Depth Separation in Approximating Benign Functions with Neural Networks Gal Vardi Daniel Reichman T. Pitassi Ohad Shamir 26 7 0 30 Jan 2021
A Convergence Theory Towards Practical Over-parameterized Deep Neural Networks Asaf Noy Yi Tian Xu Y. Aflalo Lihi Zelnik-Manor R. L. Jin 33 3 0 12 Jan 2021
Deep Neural Networks Are Effective At Learning High-Dimensional Hilbert-Valued Functions From Limited Data Ben Adcock Simone Brugiapaglia N. Dexter S. Moraga 34 29 0 11 Dec 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
Expressivity of Deep Neural Networks Ingo Gühring Mones Raslan Gitta Kutyniok 16 51 0 09 Jul 2020
Layer Sparsity in Neural Networks Mohamed Hebiri Johannes Lederer 33 10 0 28 Jun 2020
Improving Non-autoregressive Neural Machine Translation with Monolingual Data Jiawei Zhou Phillip Keung 24 26 0 02 May 2020
PERMDNN: Efficient Compressed DNN Architecture with Permuted Diagonal Matrices Chunhua Deng Siyu Liao Yi Xie Keshab K. Parhi Xuehai Qian Bo Yuan 32 93 0 23 Apr 2020
Learning Compositional Neural Information Fusion for Human Parsing Wenguan Wang Zhijie Zhang Siyuan Qi Jianbing Shen Yanwei Pang Ling Shao 3DH 33 128 0 19 Jan 2020
On Interpretability of Artificial Neural Networks: A Survey Fenglei Fan Jinjun Xiong Mengzhou Li Ge Wang AAML AI4CE 38 300 0 08 Jan 2020
Neural Contextual Bandits with UCB-based Exploration Dongruo Zhou Lihong Li Quanquan Gu 36 15 0 11 Nov 2019
Quantum enhancements for deep reinforcement learning in large spaces Sofiene Jerbi Lea M. Trenkwalder Hendrik Poulsen Nautrup H. Briegel Vedran Dunjko 21 5 0 28 Oct 2019
Optimal Function Approximation with Relu Neural Networks Bo Liu Yi Liang 25 33 0 09 Sep 2019
A Review on Deep Learning in Medical Image Reconstruction Hai-Miao Zhang Bin Dong MedIm 35 122 0 23 Jun 2019
Meta-learning Pseudo-differential Operators with Deep Neural Networks Jordi Feliu-Fabà Yuwei Fan Lexing Ying 16 39 0 16 Jun 2019
A neural network-based framework for financial model calibration Shuaiqiang Liu Anastasia Borovykh L. Grzelak C. Oosterlee 32 103 0 23 Apr 2019
Correlated Parameters to Accurately Measure Uncertainty in Deep Neural Networks K. Posch J. Pilz UQCV BDL 16 28 0 02 Apr 2019
Variational Inference to Measure Model Uncertainty in Deep Neural Networks K. Posch J. Steinbrener J. Pilz UQCV BDL 14 27 0 26 Feb 2019
Optimal Nonparametric Inference via Deep Neural Network Ruiqi Liu B. Boukai Zuofeng Shang 18 18 0 05 Feb 2019
Deep Neural Network Approximation Theory Dennis Elbrächter Dmytro Perekrestenko Philipp Grohs Helmut Bölcskei 14 207 0 08 Jan 2019
On a Sparse Shortcut Topology of Artificial Neural Networks Fenglei Fan Dayang Wang Hengtao Guo Qikui Zhu Pingkun Yan Ge Wang Hengyong Yu 38 22 0 22 Nov 2018
Stochastic Gradient Descent Optimizes Over-parameterized Deep ReLU Networks Difan Zou Yuan Cao Dongruo Zhou Quanquan Gu ODL 27 446 0 21 Nov 2018
Small ReLU networks are powerful memorizers: a tight analysis of memorization capacity Chulhee Yun S. Sra Ali Jadbabaie 20 117 0 17 Oct 2018
Understanding Weight Normalized Deep Neural Networks with Rectified Linear Units Yixi Xu Tianlin Li MQ 25 12 0 03 Oct 2018
Universal Approximation with Quadratic Deep Networks Fenglei Fan Jinjun Xiong Ge Wang PINN 17 78 0 31 Jul 2018