Universal Approximation with Deep Narrow Networks

21 May 2019

Papers citing "Universal Approximation with Deep Narrow Networks"

50 / 62 papers shown

Title
System Identification and Control Using Lyapunov-Based Deep Neural Networks without Persistent Excitation: A Concurrent Learning Approach Rebecca G. Hart Omkar Sudhir Patil Zachary I. Bell Warren E. Dixon 14 0 0 15 May 2025
Extended Fiducial Inference for Individual Treatment Effects via Deep Neural Networks Sehwan Kim F. Liang FedML 57 0 0 04 May 2025
Looped ReLU MLPs May Be All You Need as Practical Programmable Computers Yingyu Liang Zhizhou Sha Zhenmei Shi Zhao Song Yufa Zhou 101 18 0 21 Feb 2025
Kolmogorov-Arnold Fourier Networks Jusheng Zhang Yijia Fan Kaitong Cai Keze Wang 68 0 0 09 Feb 2025
Keep It Light! Simplifying Image Clustering Via Text-Free Adapters Yicen Li Haitz Sáez de Ocáriz Borde Anastasis Kratsios Paul D. McNicholas VLM 98 0 0 06 Feb 2025
Learnable polynomial, trigonometric, and tropical activations Ismail Khalfaoui-Hassani Stefan Kesselheim 64 0 0 03 Feb 2025
Deep Kalman Filters Can Filter Blanka Hovart Anastasis Kratsios Yannick Limmer Xuwei Yang 53 1 0 31 Dec 2024
TL-PCA: Transfer Learning of Principal Component Analysis Sharon Hendy Yehuda Dar 163 3 0 14 Oct 2024
Generalizable autoregressive modeling of time series through functional narratives Ran Liu Wenrui Ma Ellen L. Zippi Hadi Pouransari Jingyun Xiao ... Behrooz Mahasseni Juri Minxha Erdrin Azemi Eva L. Dyer Ali Moin AI4TS 35 1 0 10 Oct 2024
Neural networks in non-metric spaces Luca Galimberti 56 1 0 13 Jun 2024
Extremization to Fine Tune Physics Informed Neural Networks for Solving Boundary Value Problems A. Thiruthummal Sergiy Shelyag Eun-Jin Kim 33 2 0 07 Jun 2024
Information-Theoretic Generalization Bounds for Deep Neural Networks Haiyun He Christina Lee Yu 35 4 0 04 Apr 2024
A Non-monotonic Smooth Activation Function Koushik Biswas Meghana Karri Ulacs Baugci 16 1 0 16 Oct 2023
Energy-Guided Continuous Entropic Barycenter Estimation for General Costs Alexander Kolesov Petr Mokrov Igor Udovichenko Milena Gazdieva G. Pammer Anastasis Kratsios Evgeny Burnaev Alexander Korotin OT 49 2 0 02 Oct 2023
Minimum width for universal approximation using ReLU networks on compact domain Namjun Kim Chanho Min Sejun Park VLM 29 10 0 19 Sep 2023
Universal Approximation Theorem and error bounds for quantum neural networks and quantum reservoirs Lukas Gonon A. Jacquier 19 13 0 24 Jul 2023
Universal Approximation and the Topological Neural Network M. Kouritzin Daniel Richard 23 0 0 26 May 2023
Consistent Optimal Transport with Empirical Conditional Measures Piyushi Manupriya Rachit Keerti Das Sayantan Biswas S. Jagarlapudi OT 37 3 0 25 May 2023
DeepBern-Nets: Taming the Complexity of Certifying Neural Networks using Bernstein Polynomial Activations and Precise Bound Propagation Haitham Khedr Yasser Shoukry 47 5 0 22 May 2023
Hedonic Prices and Quality Adjusted Price Indices Powered by AI Patrick Bajari Zhihao Cen Victor Chernozhukov Manoj Manukonda Suhas Vijaykumar ... Ramon Huerta Junbo Li Ling Leng George Monokroussos Shan Wan 25 13 0 28 Apr 2023
Graph Neural Network Surrogates of Fair Graph Filtering Emmanouil Krasanakis Symeon Papadopoulos 32 1 0 14 Mar 2023
Alias-Free Convnets: Fractional Shift Invariance via Polynomial Activations H. Michaeli T. Michaeli Daniel Soudry 21 14 0 14 Mar 2023
On the Correctness of Automatic Differentiation for Neural Networks with Machine-Representable Parameters Wonyeol Lee Sejun Park A. Aiken PINN 21 6 0 31 Jan 2023
Stretched and measured neural predictions of complex network dynamics V. Vasiliauskaite Nino Antulov-Fantulin 33 1 0 12 Jan 2023
Deep Learning and Computational Physics (Lecture Notes) Deep Ray Orazio Pinti Assad A. Oberai PINN AI4CE 27 7 0 03 Jan 2023
Selected aspects of complex, hypercomplex and fuzzy neural networks A. Niemczynowicz R. Kycia Maciej Jaworski A. Siemaszko J. Calabuig ... Baruch Schneider Diana Berseghyan Irina Perfiljeva V. Novák Piotr Artiemjew 27 0 0 29 Dec 2022
An Introduction to Kernel and Operator Learning Methods for Homogenization by Self-consistent Clustering Analysis Owen Huang Sourav Saha Jiachen Guo Wing Kam Liu AI4CE 20 12 0 01 Dec 2022
LU decomposition and Toeplitz decomposition of a neural network Yucong Liu Simiao Jiao Lek-Heng Lim 30 7 0 25 Nov 2022
Minimal Width for Universal Property of Deep RNN Changhoon Song Geonho Hwang Jun ho Lee Myung-joo Kang 23 9 0 25 Nov 2022
Do Bayesian Neural Networks Need To Be Fully Stochastic? Mrinank Sharma Sebastian Farquhar Eric T. Nalisnick Tom Rainforth BDL 23 52 0 11 Nov 2022
Recurrent Neural Networks and Universal Approximation of Bayesian Filters A. Bishop Edwin V. Bonilla BDL 29 3 0 01 Nov 2022
On the Approximation and Complexity of Deep Neural Networks to Invariant Functions Gao Zhang Jin-Hui Wu Shao-Qun Zhang 16 0 0 27 Oct 2022
Designing Universal Causal Deep Learning Models: The Case of Infinite-Dimensional Dynamical Systems from Stochastic Analysis Luca Galimberti Anastasis Kratsios Giulia Livieri OOD 28 14 0 24 Oct 2022
Deep learning extraction of band structure parameters from density of states: a case study on trilayer graphene Paul Henderson A. Ghazaryan A. Zibrov A. Young Maksym Serbyn 16 3 0 12 Oct 2022
The (Un)Scalability of Heuristic Approximators for NP-Hard Search Problems Sumedh Pendurkar Taoan Huang Sven Koenig Guni Sharon 28 1 0 07 Sep 2022
A general approximation lower bound in $L^p$ norm, with applications to feed-forward neural networks E. M. Achour Armand Foucault Sébastien Gerchinovitz Franccois Malgouyres 32 7 0 09 Jun 2022
Designing Universal Causal Deep Learning Models: The Geometric (Hyper)Transformer Beatrice Acciaio Anastasis Kratsios G. Pammer OOD 52 20 0 31 Jan 2022
A singular Riemannian geometry approach to Deep Neural Networks I. Theoretical foundations A. Benfenati A. Marta 51 11 0 17 Dec 2021
Variational Wasserstein gradient flow JiaoJiao Fan Qinsheng Zhang Amirhossein Taghvaei Yongxin Chen 72 54 0 04 Dec 2021
Physics-enhanced deep surrogates for partial differential equations R. Pestourie Youssef Mroueh Chris Rackauckas Payel Das Steven G. Johnson PINN AI4CE 25 15 0 10 Nov 2021
SMU: smooth activation function for deep networks using smoothing maximum technique Koushik Biswas Sandeep Kumar Shilpak Banerjee A. Pandey 30 32 0 08 Nov 2021
PAC-Bayesian Learning of Aggregated Binary Activated Neural Networks with Probabilities over Representations Louis Fortier-Dubois Gaël Letarte Benjamin Leblanc Franccois Laviolette Pascal Germain UQCV 17 0 0 28 Oct 2021
Fourier Neural Networks for Function Approximation R. Subhash K. Yaswanth 28 1 0 21 Oct 2021
SAU: Smooth activation function using convolution with approximate identities Koushik Biswas Sandeep Kumar Shilpak Banerjee A. Pandey 24 6 0 27 Sep 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
ErfAct and Pserf: Non-monotonic Smooth Trainable Activation Functions Koushik Biswas Sandeep Kumar Shilpak Banerjee A. Pandey 51 13 0 09 Sep 2021
Reward-Based 1-bit Compressed Federated Distillation on Blockchain Leon Witt Usama Zafar KuoYeh Shen Felix Sattler Dan Li Wojciech Samek FedML 35 4 0 27 Jun 2021
Encoding Involutory Invariances in Neural Networks Anwesh Bhattacharya M. Mattheakis P. Protopapas 33 1 0 07 Jun 2021
Efficient and Accurate Gradients for Neural SDEs Patrick Kidger James Foster Xuechen Li Terry Lyons DiffM 24 60 0 27 May 2021
Neural network architectures using min-plus algebra for solving certain high dimensional optimal control problems and Hamilton-Jacobi PDEs Jérome Darbon P. Dower Tingwei Meng 8 22 0 07 May 2021