Neural Networks Trained by Weight Permutation are Universal Approximators
Fuente:
arXiv
Saved in:
| Main Authors: | Cai, Yongqiang, Chen, Gaohang, Qiao, Zhonghua |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
MonoKAN: Certified Monotonic Kolmogorov-Arnold Network
by: Polo-Molina, Alejandro, et al.
Published: (2024)
by: Polo-Molina, Alejandro, et al.
Published: (2024)
Universal approximation theorem for neural networks with inputs from a topological vector space
by: Ismailov, Vugar
Published: (2024)
by: Ismailov, Vugar
Published: (2024)
Efficient Approximation to Analytic and $L^p$ functions by Height-Augmented ReLU Networks
by: Li, ZeYu, et al.
Published: (2026)
by: Li, ZeYu, et al.
Published: (2026)
Beyond Universal Approximation Theorems: Algorithmic Uniform Approximation by Neural Networks Trained with Noisy Data
by: Kratsios, Anastasis, et al.
Published: (2025)
by: Kratsios, Anastasis, et al.
Published: (2025)
Addressing common misinterpretations of KART and UAT in neural network literature
by: Ismailov, Vugar
Published: (2024)
by: Ismailov, Vugar
Published: (2024)
Composition of Relational Features with an Application to Explaining Black-Box Predictors
by: Srinivasan, Ashwin, et al.
Published: (2022)
by: Srinivasan, Ashwin, et al.
Published: (2022)
Towards Understanding the Link Between Modularity and Performance in Neural Networks for Reinforcement Learning
by: Munn, Humphrey, et al.
Published: (2022)
by: Munn, Humphrey, et al.
Published: (2022)
Deep Neural Networks: A Formulation Via Non-Archimedean Analysis
by: Zúñiga-Galindo, W. A.
Published: (2024)
by: Zúñiga-Galindo, W. A.
Published: (2024)
Structural Correspondence and Universal Approximation in Diagonal plus Low-Rank Neural Networks
by: Chen, Ying, et al.
Published: (2026)
by: Chen, Ying, et al.
Published: (2026)
Bridging the Gap Between Approximation and Learning via Optimal Approximation by ReLU MLPs of Maximal Regularity
by: Hong, Ruiyang, et al.
Published: (2024)
by: Hong, Ruiyang, et al.
Published: (2024)
Pointer Networks Trained Better via Evolutionary Algorithms
by: Zhong, Muyao, et al.
Published: (2023)
by: Zhong, Muyao, et al.
Published: (2023)
Fractional Artificial Neural Networks for Growth Models
by: Najera-Tinoco, Juan Carlos, et al.
Published: (2025)
by: Najera-Tinoco, Juan Carlos, et al.
Published: (2025)
Game-Theoretic Gradient Control for Robust Neural Network Training
by: Zaitseva, Maria, et al.
Published: (2025)
by: Zaitseva, Maria, et al.
Published: (2025)
P1-KAN: an effective Kolmogorov-Arnold network with application to hydraulic valley optimization
by: Warin, Xavier
Published: (2024)
by: Warin, Xavier
Published: (2024)
A parametric activation function based on Wendland RBF
by: Darehmiraki, Majid
Published: (2025)
by: Darehmiraki, Majid
Published: (2025)
Universal Approximation Constraints of Narrow ResNets: The Tunnel Effect
by: Kuehn, Christian, et al.
Published: (2026)
by: Kuehn, Christian, et al.
Published: (2026)
Embedding Dimension Lower Bounds for Universality of Deep Sets and Janossy Pooling
by: Syed, Ali, et al.
Published: (2026)
by: Syed, Ali, et al.
Published: (2026)
Approximation Error and Complexity Bounds for ReLU Networks on Low-Regular Function Spaces
by: Davis, Owen, et al.
Published: (2024)
by: Davis, Owen, et al.
Published: (2024)
AiGAS-dEVL-RC: An Adaptive Growing Neural Gas Model for Recurrently Drifting Unsupervised Data Streams
by: Arostegi, Maria, et al.
Published: (2025)
by: Arostegi, Maria, et al.
Published: (2025)
Task-Synchronized Recurrent Neural Networks
by: Lukoševičius, Mantas, et al.
Published: (2022)
by: Lukoševičius, Mantas, et al.
Published: (2022)
Minimum Width of Leaky-ReLU Neural Networks for Uniform Universal Approximation
by: Li, Li'ang, et al.
Published: (2023)
by: Li, Li'ang, et al.
Published: (2023)
NACHOS: Neural Architecture Search for Hardware Constrained Early Exit Neural Networks
by: Gambella, Matteo, et al.
Published: (2024)
by: Gambella, Matteo, et al.
Published: (2024)
Proximity-Based Evidence Retrieval for Uncertainty-Aware Neural Networks
by: Gharoun, Hassan, et al.
Published: (2025)
by: Gharoun, Hassan, et al.
Published: (2025)
Uncertainty-Aware Post-Hoc Calibration: Mitigating Confidently Incorrect Predictions Beyond Calibration Metrics
by: Gharoun, Hassan, et al.
Published: (2025)
by: Gharoun, Hassan, et al.
Published: (2025)
Towards Solving Polynomial-Objective Integer Programming with Hypergraph Neural Networks
by: Li, Minshuo, et al.
Published: (2026)
by: Li, Minshuo, et al.
Published: (2026)
From Embeddings to Equations: Genetic-Programming Surrogates for Interpretable Transformer Classification
by: Khorshidi, Mohammad Sadegh, et al.
Published: (2025)
by: Khorshidi, Mohammad Sadegh, et al.
Published: (2025)
Random Feature Spiking Neural Networks
by: Gollwitzer, Maximilian, et al.
Published: (2025)
by: Gollwitzer, Maximilian, et al.
Published: (2025)
Beyond LLMs, Sparse Distributed Memory, and Neuromorphics <A Hyper-Dimensional SRAM-CAM "VaCoAl" for Ultra-High Speed, Ultra-Low Power, and Low Cost>
by: Chuma, Hiroyuki, et al.
Published: (2026)
by: Chuma, Hiroyuki, et al.
Published: (2026)
Reconstructing shared dynamics with a deep neural network
by: Benkő, Zsigmond, et al.
Published: (2021)
by: Benkő, Zsigmond, et al.
Published: (2021)
Quantifying The Limits of AI Reasoning: Systematic Neural Network Representations of Algorithms
by: Kratsios, Anastasis, et al.
Published: (2025)
by: Kratsios, Anastasis, et al.
Published: (2025)
Unveiling the frontiers of deep learning: innovations shaping diverse domains
by: Ahmed, Shams Forruque, et al.
Published: (2023)
by: Ahmed, Shams Forruque, et al.
Published: (2023)
Implementing Online Reinforcement Learning with Clustering Neural Networks
by: Smith, James E.
Published: (2024)
by: Smith, James E.
Published: (2024)
Structure-Preserving Reconstruction of Convex Lipschitz Functionals on Hilbert Spaces from Finite Samples
by: Kratsios, Anastasis
Published: (2026)
by: Kratsios, Anastasis
Published: (2026)
Adjusting Dynamics of Hopfield Neural Network via Time-variant Stimulus
by: Peng, Xuenan, et al.
Published: (2024)
by: Peng, Xuenan, et al.
Published: (2024)
An accurate flatness measure to estimate the generalization performance of CNN models
by: Taleghani, Rahman, et al.
Published: (2026)
by: Taleghani, Rahman, et al.
Published: (2026)
NervePool: A Simplicial Pooling Layer
by: Scullen, Sarah McGuire, et al.
Published: (2023)
by: Scullen, Sarah McGuire, et al.
Published: (2023)
Planarian Neural Networks: Evolutionary Patterns from Basic Bilateria Shaping Modern Artificial Neural Network Architectures
by: Huang, Ziyuan, et al.
Published: (2025)
by: Huang, Ziyuan, et al.
Published: (2025)
Rapid training of Hamiltonian graph networks using random features
by: Rahma, Atamert, et al.
Published: (2025)
by: Rahma, Atamert, et al.
Published: (2025)
Approximation and Gradient Descent Training with Neural Networks
by: Welper, G.
Published: (2024)
by: Welper, G.
Published: (2024)
A Minimal Control Family of Dynamical Systems for Universal Approximation
by: Duan, Yifei, et al.
Published: (2023)
by: Duan, Yifei, et al.
Published: (2023)
Similar Items
-
MonoKAN: Certified Monotonic Kolmogorov-Arnold Network
by: Polo-Molina, Alejandro, et al.
Published: (2024) -
Universal approximation theorem for neural networks with inputs from a topological vector space
by: Ismailov, Vugar
Published: (2024) -
Efficient Approximation to Analytic and $L^p$ functions by Height-Augmented ReLU Networks
by: Li, ZeYu, et al.
Published: (2026) -
Beyond Universal Approximation Theorems: Algorithmic Uniform Approximation by Neural Networks Trained with Noisy Data
by: Kratsios, Anastasis, et al.
Published: (2025) -
Addressing common misinterpretations of KART and UAT in neural network literature
by: Ismailov, Vugar
Published: (2024)