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Universal Function Approximation by Deep Neural Nets with Bounded Width and ReLU Activations

9 August 2017

Papers citing "Universal Function Approximation by Deep Neural Nets with Bounded Width and ReLU Activations"

50 / 161 papers shown

Title
Upper Approximation Bounds for Neural Oscillators Zifeng Huang Konstantin M. Zuev Yong Xia Michael Beer 44 0 0 30 Nov 2025
An in-depth look at approximation via deep and narrow neural networks Joris Dommel Sven A. Wegner 84 0 0 08 Oct 2025
Beyond Universal Approximation Theorems: Algorithmic Uniform Approximation by Neural Networks Trained with Noisy Data Anastasis Kratsios Tin Sum Cheng Daniel Roy AAML 148 0 0 31 Aug 2025
On the Limits of Hierarchically Embedded Logic in Classical Neural Networks Bill Cochran NAI 52 0 0 28 Jul 2025
FSL-SAGE: Accelerating Federated Split Learning via Smashed Activation Gradient Estimation Srijith Nair Michael Lin Amirreza Talebi Peizhong Ju Elizabeth S. Bentley Jia Liu FedML 161 0 0 29 May 2025
Time to Spike? Understanding the Representational Power of Spiking Neural Networks in Discrete Time Duc Anh Nguyen Ernesto Araya Adalbert Fono Gitta Kutyniok 487 0 0 23 May 2025
Explicit neural network classifiers for non-separable data Patrícia Muñoz Ewald 151 1 0 25 Apr 2025
Neural network-enhanced integrators for simulating ordinary differential equations Amine Othmane Kathrin Flaßkamp 130 0 0 07 Apr 2025
A Theory of Machine Understanding via the Minimum Description Length Principle Canlin Zhang Xiuwen Liu 317 0 0 01 Apr 2025
On the Expressiveness of Rational ReLU Neural Networks With Bounded DepthInternational Conference on Learning Representations (ICLR), 2025 Gennadiy Averkov Christopher Hojny Maximilian Merkert 293 7 0 10 Feb 2025
Orthogonal Representation Learning for Estimating Causal Quantities Valentyn Melnychuk Dennis Frauen Jonas Schweisthal Stefan Feuerriegel CML OOD BDL 418 4 0 06 Feb 2025
A deformation-based framework for learning solution mappings of PDEs defined on varying domains Shanshan Xiao Pengzhan Jin Yifa Tang 232 2 0 02 Dec 2024
Neural Hamilton: Can A.I. Understand Hamiltonian Mechanics? Tae-Geun Kim Seong Chan Park 235 0 0 28 Oct 2024
Decomposition of Equivariant Maps via Invariant Maps: Application to Universal Approximation under Symmetry Akiyoshi Sannai Yuuki Takai Matthieu Cordonnier 897 0 0 25 Sep 2024
Numerical Approximation Capacity of Neural Networks with Bounded Parameters: Do Limits Exist, and How Can They Be Measured? Li Liu Tengchao Yu Heng Yong 104 1 0 25 Sep 2024
Machine-learning based high-bandwidth magnetic sensing Galya Haim Stefano Martina John Howell Nir Bar-Gill Filippo Caruso 123 0 0 19 Sep 2024
Constructive Universal Approximation and Finite Sample Memorization by Narrow Deep ReLU Networks Martín Hernández Enrique Zuazua 158 1 0 10 Sep 2024
Additive regularization schedule for neural architecture search M. Potanin Kirill Vayser Vadim Strijov 83 0 0 18 Jun 2024
Deep Neural Networks are Adaptive to Function Regularity and Data Distribution in Approximation and Estimation Hao Liu Jiahui Cheng Wenjing Liao 138 1 0 08 Jun 2024
Lower Bounds on the Expressivity of Recurrent Neural Language Models Anej Svete Franz Nowak Anisha Mohamed Sahabdeen Robert Bamler 226 0 0 29 May 2024
Approximation Error and Complexity Bounds for ReLU Networks on Low-Regular Function Spaces Owen Davis Gianluca Geraci Mohammad Motamed 156 2 0 10 May 2024
PNeRV: Enhancing Spatial Consistency via Pyramidal Neural Representation for Videos Qi Zhao M. Salman Asif Zhan Ma 206 7 0 13 Apr 2024
Learning solution operators of PDEs defined on varying domains via MIONet Shanshan Xiao Pengzhan Jin Yifa Tang 268 6 0 23 Feb 2024
Distal Interference: Exploring the Limits of Model-Based Continual Learning H. V. Deventer Anna Sergeevna Bosman 104 1 0 13 Feb 2024
Towards Understanding the Word Sensitivity of Attention Layers: A Study via Random FeaturesInternational Conference on Machine Learning (ICML), 2024 Simone Bombari Marco Mondelli 237 6 0 05 Feb 2024
Weakly Convex Regularisers for Inverse Problems: Convergence of Critical Points and Primal-Dual Optimisation Zakhar Shumaylov Jeremy Budd Subhadip Mukherjee Carola-Bibiane Schönlieb 328 17 0 01 Feb 2024
A Survey on Statistical Theory of Deep Learning: Approximation, Training Dynamics, and Generative ModelsAnnual Review of Statistics and Its Application (ARSIA), 2024 Namjoon Suh Guang Cheng MedIm 285 17 0 14 Jan 2024
Reverse Engineering Deep ReLU Networks An Optimization-based Algorithm Mehrab Hamidi 221 0 0 07 Dec 2023
Commutative Width and Depth Scaling in Deep Neural Networks Soufiane Hayou 170 2 0 02 Oct 2023
Fundamental Limits of Deep Learning-Based Binary Classifiers Trained with Hinge Loss T. Getu Georges Kaddoum M. Bennis 282 1 0 13 Sep 2023
Deep Semi-Supervised Anomaly Detection for Finding Fraud in the Futures Market Timothy DeLise 90 2 0 31 Aug 2023
Predicting and explaining nonlinear material response using deep Physically Guided Neural Networks with Internal VariablesMathematics and mechanics of solids (MMS), 2023 Javier Orera-Echeverria J. Ayensa-Jiménez Manuel Doblaré 182 3 0 07 Aug 2023
Optimal Approximation and Learning Rates for Deep Convolutional Neural Networks Shao-Bo Lin 140 1 0 07 Aug 2023
AbDiffuser: Full-Atom Generation of in vitro Functioning AntibodiesNeural Information Processing Systems (NeurIPS), 2023 Karolis Martinkus J. Ludwiczak Kyunghyun Cho Weishao Lian J. Lafrance-Vanasse ... A. Rajpal Yongpeng Wu Richard Bonneau Vladimir Gligorijević Andreas Loukas DiffM 251 63 0 28 Jul 2023
Why do CNNs excel at feature extraction? A mathematical explanation V. Nandakumar Arush Tagade Tongliang Liu FAtt 91 1 0 03 Jul 2023
Data Topology-Dependent Upper Bounds of Neural Network Widths Sangmin Lee Jong Chul Ye 197 1 0 25 May 2023
Deep neural networks have an inbuilt Occam's razorNature Communications (Nat. Commun.), 2023 Chris Mingard Henry Rees Guillermo Valle Pérez A. Louis UQCV BDL 256 16 0 13 Apr 2023
SGL: Structure Guidance Learning for Camera Localization Xudong Zhang Shuang Gao Xiaohu Nan Haikuan Ning Yuchen Yang Yishan Ping Jixiang Wan Shuzhou Dong Jijunnan Li Yandong Guo 175 0 0 12 Apr 2023
Neural Network Predicts Ion Concentration Profiles under NanoconfinementJournal of Chemical Physics (JCP), 2023 Zhonglin Cao Yuyang Wang Cooper Lorsung A. Farimani 198 1 0 10 Apr 2023
A Deep Learning Approach Towards Generating High-fidelity Diverse Synthetic Battery DatasetsIEEE transactions on industry applications (IEEE Trans. Ind. Appl.), 2023 Janamejaya Channegowda Vageesh Maiya Chaitanya Lingaraj 114 5 0 09 Apr 2023
Non-asymptotic approximations of Gaussian neural networks via second-order Poincaré inequalitiesSymposium on Advances in Approximate Bayesian Inference (AABI), 2023 Alberto Bordino Stefano Favaro S. Fortini 205 10 0 08 Apr 2023
Error convergence and engineering-guided hyperparameter search of PINNs: towards optimized I-FENN performanceSocial Science Research Network (SSRN), 2023 Panos Pantidis Habiba Eldababy Christopher Miguel Tagle M. Mobasher 211 26 0 03 Mar 2023
Lower Bounds on the Depth of Integral ReLU Neural Networks via Lattice PolytopesInternational Conference on Learning Representations (ICLR), 2023 Christian Haase Christoph Hertrich Georg Loho 177 28 0 24 Feb 2023
Width and Depth Limits Commute in Residual NetworksInternational Conference on Machine Learning (ICML), 2023 Soufiane Hayou Greg Yang 182 17 0 01 Feb 2023
Formalizing Piecewise Affine Activation Functions of Neural Networks in CoqNASA Formal Methods (NFM), 2023 A. Aleksandrov Kim Völlinger 90 6 0 30 Jan 2023
Effects of Data Geometry in Early Deep LearningNeural Information Processing Systems (NeurIPS), 2022 Saket Tiwari George Konidaris 301 7 0 29 Dec 2022
On Solution Functions of Optimization: Universal Approximation and Covering Number BoundsAAAI Conference on Artificial Intelligence (AAAI), 2022 Ming Jin Vanshaj Khattar Harshal D. Kaushik Bilgehan Sel R. Jia 99 14 0 02 Dec 2022
Optimal Approximation Rates for Deep ReLU Neural Networks on Sobolev and Besov SpacesJournal of machine learning research (JMLR), 2022 Jonathan W. Siegel 549 43 0 25 Nov 2022
Factor Augmented Sparse Throughput Deep ReLU Neural Networks for High Dimensional RegressionJournal of the American Statistical Association (JASA), 2022 Jianqing Fan Yihong Gu 401 35 0 05 Oct 2022
On the infinite-depth limit of finite-width neural networks Soufiane Hayou 209 24 0 03 Oct 2022