Saved in:
| Main Authors: | Chen, Haozhe, Correa, Andres Felipe Duque, Wolf, Guy, Moon, Kevin R. |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2406.03396 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Quantum Harmonic Analysis and the Structure in Data: Augmentation
by: Doerfler, Monika, et al.
Published: (2025)
by: Doerfler, Monika, et al.
Published: (2025)
Spherical Analysis of Learning Nonlinear Functionals
by: Yang, Zhenyu, et al.
Published: (2024)
by: Yang, Zhenyu, et al.
Published: (2024)
The Function Representation of Artificial Neural Network
by: Ma, Zhongkui
Published: (2019)
by: Ma, Zhongkui
Published: (2019)
Learning Orthonormal Bases for Function Spaces
by: Kamkari, Hamidreza, et al.
Published: (2026)
by: Kamkari, Hamidreza, et al.
Published: (2026)
Bayesian Optimization through Gaussian Cox Process Models for Spatio-temporal Data
by: Mei, Yongsheng, et al.
Published: (2024)
by: Mei, Yongsheng, et al.
Published: (2024)
Langevin Monte-Carlo Provably Learns Depth Two Neural Nets at Any Size and Data
by: Kumar, Dibyakanti, et al.
Published: (2025)
by: Kumar, Dibyakanti, et al.
Published: (2025)
Understanding Transfer Learning via Mean-field Analysis
by: Aminian, Gholamali, et al.
Published: (2024)
by: Aminian, Gholamali, et al.
Published: (2024)
A Fractional Fox H-Function Kernel for Support Vector Machines: Robust Classification via Weighted Transmutation Operators
by: Dorrego, Gustavo
Published: (2026)
by: Dorrego, Gustavo
Published: (2026)
Fisher-Rao Gradient Flow: Geodesic Convexity and Functional Inequalities
by: Carrillo, José A., et al.
Published: (2024)
by: Carrillo, José A., et al.
Published: (2024)
Convergence Analysis of Max-Min Exponential Neural Network Operators in Orlicz Space
by: Pradhan, Satyaranjan, et al.
Published: (2025)
by: Pradhan, Satyaranjan, et al.
Published: (2025)
How Analysis Can Teach Us the Optimal Way to Design Neural Operators
by: Le, Vu-Anh, et al.
Published: (2024)
by: Le, Vu-Anh, et al.
Published: (2024)
Non-Asymptotic Stability and Consistency Guarantees for Physics-Informed Neural Networks via Coercive Operator Analysis
by: Katende, Ronald
Published: (2025)
by: Katende, Ronald
Published: (2025)
Neural Hilbert Ladders: Multi-Layer Neural Networks in Function Space
by: Chen, Zhengdao
Published: (2023)
by: Chen, Zhengdao
Published: (2023)
Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning
by: Berner, Julius, et al.
Published: (2025)
by: Berner, Julius, et al.
Published: (2025)
A Kernel-Based Approach for Modelling Gaussian Processes with Functional Information
by: Brown, D. Andrew, et al.
Published: (2022)
by: Brown, D. Andrew, et al.
Published: (2022)
Sparse-Aware Neural Networks for Nonlinear Functionals: Mitigating the Exponential Dependence on Dimension
by: Li, Jianfei, et al.
Published: (2026)
by: Li, Jianfei, et al.
Published: (2026)
Integrating Product Coefficients for Improved 3D LiDAR Data Classification
by: Medina, Patricia
Published: (2025)
by: Medina, Patricia
Published: (2025)
An Interpretable Approach to Load Profile Forecasting in Power Grids using Galerkin-Approximated Koopman Pseudospectra
by: Tavasoli, Ali, et al.
Published: (2023)
by: Tavasoli, Ali, et al.
Published: (2023)
Poincaré Inequality for Local Log-Polyak-Lojasiewicz Measures : Non-asymptotic Analysis in Low-temperature Regime
by: Gong, Yun, et al.
Published: (2025)
by: Gong, Yun, et al.
Published: (2025)
Do stable neural networks exist for classification problems? -- A new view on stability in AI
by: Liu, Z. N. D., et al.
Published: (2024)
by: Liu, Z. N. D., et al.
Published: (2024)
On Rank-Dependent Generalisation Error Bounds for Transformers
by: Truong, Lan V.
Published: (2024)
by: Truong, Lan V.
Published: (2024)
A unified Fourier slice method to derive ridgelet transform for a variety of depth-2 neural networks
by: Sonoda, Sho, et al.
Published: (2024)
by: Sonoda, Sho, et al.
Published: (2024)
Hypothesis Spaces for Deep Learning
by: Wang, Rui, et al.
Published: (2024)
by: Wang, Rui, et al.
Published: (2024)
Neural reproducing kernel Banach spaces and representer theorems for deep networks
by: Bartolucci, Francesca, et al.
Published: (2024)
by: Bartolucci, Francesca, et al.
Published: (2024)
Neural networks in non-metric spaces
by: Galimberti, Luca
Published: (2024)
by: Galimberti, Luca
Published: (2024)
Controlled Learning of Pointwise Nonlinearities in Neural-Network-Like Architectures
by: Unser, Michael, et al.
Published: (2024)
by: Unser, Michael, et al.
Published: (2024)
Stability of sorting based embeddings
by: Balan, Radu, et al.
Published: (2024)
by: Balan, Radu, et al.
Published: (2024)
Approximation by Steklov Neural Network Operators
by: Karaman, S. N., et al.
Published: (2024)
by: Karaman, S. N., et al.
Published: (2024)
Theory-to-Practice Gap for Neural Networks and Neural Operators
by: Grohs, Philipp, et al.
Published: (2025)
by: Grohs, Philipp, et al.
Published: (2025)
Quantitative Sobolev Approximation Bounds for Neural Operators with Empirical Validation on Burgers Equation
by: Hao, Nicole
Published: (2026)
by: Hao, Nicole
Published: (2026)
Universal approximation with complex-valued deep narrow neural networks
by: Geuchen, Paul, et al.
Published: (2023)
by: Geuchen, Paul, et al.
Published: (2023)
Approximation of Permutation Invariant Polynomials by Transformers: Efficient Construction in Column-Size
by: Takeshita, Naoki, et al.
Published: (2025)
by: Takeshita, Naoki, et al.
Published: (2025)
Sparse Representer Theorems for Learning in Reproducing Kernel Banach Spaces
by: Wang, Rui, et al.
Published: (2023)
by: Wang, Rui, et al.
Published: (2023)
Rough kernel hedging
by: Cirone, Nicola Muca, et al.
Published: (2025)
by: Cirone, Nicola Muca, et al.
Published: (2025)
On shallow feedforward neural networks with inputs from a topological space
by: Ismailov, Vugar
Published: (2025)
by: Ismailov, Vugar
Published: (2025)
Horizon Activation Mapping for Neural Networks in Time Series Forecasting
by: Hans, Krupakar, et al.
Published: (2026)
by: Hans, Krupakar, et al.
Published: (2026)
Koopman-based generalization bound: New aspect for full-rank weights
by: Hashimoto, Yuka, et al.
Published: (2023)
by: Hashimoto, Yuka, et al.
Published: (2023)
Construction of generalized samplets in Banach spaces
by: Balazs, Peter, et al.
Published: (2024)
by: Balazs, Peter, et al.
Published: (2024)
Unified generalization analysis for physics informed neural networks
by: Hashimoto, Yuka, et al.
Published: (2026)
by: Hashimoto, Yuka, et al.
Published: (2026)
Optimal lower Lipschitz bounds for ReLU layers, saturation, and phase retrieval
by: Freeman, Daniel, et al.
Published: (2025)
by: Freeman, Daniel, et al.
Published: (2025)
Similar Items
-
Quantum Harmonic Analysis and the Structure in Data: Augmentation
by: Doerfler, Monika, et al.
Published: (2025) -
Spherical Analysis of Learning Nonlinear Functionals
by: Yang, Zhenyu, et al.
Published: (2024) -
The Function Representation of Artificial Neural Network
by: Ma, Zhongkui
Published: (2019) -
Learning Orthonormal Bases for Function Spaces
by: Kamkari, Hamidreza, et al.
Published: (2026) -
Bayesian Optimization through Gaussian Cox Process Models for Spatio-temporal Data
by: Mei, Yongsheng, et al.
Published: (2024)