Deep Neural Networks: A Formulation Via Non-Archimedean Analysis
Fuente:
arXiv
Saved in:
| Main Author: | Zúñiga-Galindo, W. A. |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Neural Networks Trained by Weight Permutation are Universal Approximators
by: Cai, Yongqiang, et al.
Published: (2024)
by: Cai, Yongqiang, et al.
Published: (2024)
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)
Universal approximation theorem for neural networks with inputs from a topological vector space
by: Ismailov, Vugar
Published: (2024)
by: Ismailov, Vugar
Published: (2024)
From Taylor Series to Fourier Synthesis: The Periodic Linear Unit
by: Kudo, Shiko
Published: (2025)
by: Kudo, Shiko
Published: (2025)
On the Principles of ReLU Networks with One Hidden Layer
by: Huang, Changcun
Published: (2024)
by: Huang, Changcun
Published: (2024)
Trustworthy AI in numerics: On verification algorithms for neural network-based PDE solvers
by: Haugen, Emil, et al.
Published: (2025)
by: Haugen, Emil, et al.
Published: (2025)
MonoKAN: Certified Monotonic Kolmogorov-Arnold Network
by: Polo-Molina, Alejandro, et al.
Published: (2024)
by: Polo-Molina, Alejandro, et al.
Published: (2024)
Towards Solving Polynomial-Objective Integer Programming with Hypergraph Neural Networks
by: Li, Minshuo, et al.
Published: (2026)
by: Li, Minshuo, et al.
Published: (2026)
A General Weighting Theory for Ensemble Learning: Beyond Variance Reduction via Spectral and Geometric Structure
by: Fokoué, Ernest
Published: (2025)
by: Fokoué, Ernest
Published: (2025)
Sharp Lower Bounds on Interpolation by Deep ReLU Neural Networks at Irregularly Spaced Data
by: Siegel, Jonathan W.
Published: (2023)
by: Siegel, Jonathan W.
Published: (2023)
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)
Ridge Kernel Averaging and Uniform Approximation
by: Tian, James
Published: (2025)
by: Tian, James
Published: (2025)
Equidistribution-based training of Free Knot Splines and ReLU Neural Networks
by: Appella, Simone, et al.
Published: (2024)
by: Appella, Simone, et al.
Published: (2024)
Deep Vision: A Formal Proof of Wolstenholmes Theorem in Lean 4
by: Linhares, Alexandre
Published: (2026)
by: Linhares, Alexandre
Published: (2026)
Hyperbolic trigonometric functions as approximation kernels and their properties II: Wavelets
by: Buhmann, M., et al.
Published: (2025)
by: Buhmann, M., et al.
Published: (2025)
SUPN: Shallow Universal Polynomial Networks
by: Morrow, Zachary, et al.
Published: (2025)
by: Morrow, Zachary, et al.
Published: (2025)
A Construction of $C^{r}$ Conforming Finite Elements on the Alfeld Split in Any Dimension
by: Lin, Ting, et al.
Published: (2026)
by: Lin, Ting, et al.
Published: (2026)
Discretization Error of Fourier Neural Operators
by: Lanthaler, Samuel, et al.
Published: (2024)
by: Lanthaler, Samuel, et al.
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)
Fourier Residual Networks Achieve Spectral Accuracy for Discontinuous Functions
by: Davis, Owen, et al.
Published: (2026)
by: Davis, Owen, et al.
Published: (2026)
Learning to Integrate
by: Ernst, Oliver G., et al.
Published: (2025)
by: Ernst, Oliver G., et al.
Published: (2025)
Contraction, Criticality, and Capacity: A Dynamical-Systems Perspective on Echo-State Networks
by: Singh, Pradeep, et al.
Published: (2025)
by: Singh, Pradeep, et al.
Published: (2025)
A data-driven Fourier-mixture neural-network method for density estimation
by: Dang, Duy-Minh, et al.
Published: (2026)
by: Dang, Duy-Minh, et al.
Published: (2026)
Learning Contractive Integral Operators with Fredholm Integral Neural Operators
by: Georgiou, Kyriakos C., et al.
Published: (2026)
by: Georgiou, Kyriakos C., et al.
Published: (2026)
On the algorithmic construction of deep ReLU networks
by: Huybrechs, Daan
Published: (2025)
by: Huybrechs, Daan
Published: (2025)
Transformers Can Solve Non-Linear and Non-Markovian Filtering Problems in Continuous Time For Conditionally Gaussian Signals
by: Horvath, Blanka, et al.
Published: (2023)
by: Horvath, Blanka, et al.
Published: (2023)
Derivative-Informed Fourier Neural Operator: Universal Approximation and Applications to PDE-Constrained Optimization
by: Yao, Boyuan, et al.
Published: (2025)
by: Yao, Boyuan, et al.
Published: (2025)
Uniform Approximation with Quadratic Neural Networks
by: Abdeljawad, Ahmed
Published: (2022)
by: Abdeljawad, Ahmed
Published: (2022)
Gowers norms for linearly recurrent numeration systems
by: Jelinek, Pascal
Published: (2025)
by: Jelinek, Pascal
Published: (2025)
Universal Approximation of Dynamical Systems by Semi-Autonomous Neural ODEs and Applications
by: Li, Ziqian, et al.
Published: (2024)
by: Li, Ziqian, et al.
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)
The Thue-Morse Transform
by: Cloitre, Benoit
Published: (2026)
by: Cloitre, Benoit
Published: (2026)
Congruence Classes of Supporting the Erdös-Straus Conjecture I: Tame Solutions
by: Xu, Xiaoping
Published: (2026)
by: Xu, Xiaoping
Published: (2026)
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)
On Fibonacci Ensembles: An Alternative Approach to Ensemble Learning Inspired by the Timeless Architecture of the Golden Ratio
by: Fokoué, Ernest
Published: (2025)
by: Fokoué, Ernest
Published: (2025)
A method for determining the mod-$p^k$ behaviour of recursive sequences
by: Krattenthaler, Christian, et al.
Published: (2015)
by: Krattenthaler, Christian, et al.
Published: (2015)
Learnable Viscosity Modulation in Physics-Informed Neural Networks for Incompressible Flow Reconstruction
by: Xu, Ke, et al.
Published: (2026)
by: Xu, Ke, et al.
Published: (2026)
Deep Learning Based on Randomized Quasi-Monte Carlo Method for Solving Linear Kolmogorov Partial Differential Equation
by: Xiao, Jichang, et al.
Published: (2023)
by: Xiao, Jichang, et al.
Published: (2023)
Asymptotic and non-asymptotic results for a binary additive problem involving Piatetski-Shapiro numbers
by: Yoshida, Yuuya
Published: (2024)
by: Yoshida, Yuuya
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)
Similar Items
-
Neural Networks Trained by Weight Permutation are Universal Approximators
by: Cai, Yongqiang, et al.
Published: (2024) -
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) -
Universal approximation theorem for neural networks with inputs from a topological vector space
by: Ismailov, Vugar
Published: (2024) -
From Taylor Series to Fourier Synthesis: The Periodic Linear Unit
by: Kudo, Shiko
Published: (2025) -
On the Principles of ReLU Networks with One Hidden Layer
by: Huang, Changcun
Published: (2024)