Copertina

On Expressivity of Height in Neural Networks

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Fan, Feng-Lei, Li, Ze-Yu, Xiong, Huan, Zeng, Tieyong
Natura:	Preprint
Pubblicazione:	2023
Soggetti:	Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Efficient Approximation to Analytic and $L^p$ functions by Height-Augmented ReLU Networks
di: Li, ZeYu, et al.
Pubblicazione: (2026)

Deep ReLU Networks Have Surprisingly Simple Polytopes
di: Fan, Feng-Lei, et al.
Pubblicazione: (2023)

No One-Size-Fits-All Neurons: Task-based Neurons for Artificial Neural Networks
di: Fan, Feng-Lei, et al.
Pubblicazione: (2024)

Neural Network Approximation: A View from Polytope Decomposition
di: Li, ZeYu, et al.
Pubblicazione: (2026)

DGNN: A Neural PDE Solver Induced by Discontinuous Galerkin Methods
di: Chen, Guanyu, et al.
Pubblicazione: (2025)

Towards Bridging Generalization and Expressivity of Graph Neural Networks
di: Li, Shouheng, et al.
Pubblicazione: (2024)

Full-Spectrum Graph Neural Networks: Expressive and Scalable
di: Wang, Xiaohan, et al.
Pubblicazione: (2026)

Tropical Expressivity of Neural Networks
di: Lezeau, Paul, et al.
Pubblicazione: (2024)

The Expressive Power of Graph Neural Networks: A Survey
di: Zhang, Bingxu, et al.
Pubblicazione: (2023)

On the Expressive Power of Graph Neural Networks
di: Nalwade, Ashwin, et al.
Pubblicazione: (2024)

The WidthWall: A Strict Expressivity Hierarchy for Hypergraph Neural Networks
di: Jiang, Fengqing, et al.
Pubblicazione: (2026)

Towards Dynamic Graph Neural Networks with Provably High-Order Expressive Power
di: Wang, Zhe, et al.
Pubblicazione: (2024)

Homomorphism Expressivity of Spectral Invariant Graph Neural Networks
di: Gai, Jingchu, et al.
Pubblicazione: (2025)

Invariant-Stratified Propagation for Expressive Graph Neural Networks
di: Hevapathige, Asela, et al.
Pubblicazione: (2026)

On the Relationship Between Robustness and Expressivity of Graph Neural Networks
di: Kummer, Lorenz, et al.
Pubblicazione: (2025)

Towards Expressive Spectral-Temporal Graph Neural Networks for Time Series Forecasting
di: Jin, Ming, et al.
Pubblicazione: (2023)

The Logical Expressiveness of Topological Neural Networks
di: Akbari, Amirreza, et al.
Pubblicazione: (2026)

Weisfeiler Lehman Test on Combinatorial Complexes: Generalized Expressive Power of Topological Neural Networks
di: Chen, Jiawen, et al.
Pubblicazione: (2026)

On the Expressive Power of Geometric Graph Neural Networks
di: Joshi, Chaitanya K., et al.
Pubblicazione: (2023)

On the Expressiveness of Softmax Attention: A Recurrent Neural Network Perspective
di: Mongaras, Gabriel, et al.
Pubblicazione: (2025)

Generalization, Expressivity, and Universality of Graph Neural Networks on Attributed Graphs
di: Rauchwerger, Levi, et al.
Pubblicazione: (2024)

Random Search Neural Networks for Efficient and Expressive Graph Learning
di: Ito, Michael, et al.
Pubblicazione: (2025)

Improving Expressive Power of Spectral Graph Neural Networks with Eigenvalue Correction
di: Lu, Kangkang, et al.
Pubblicazione: (2024)

Expressive Power of Deep Networks on Manifolds: Simultaneous Approximation
di: Zhou, Hanfei, et al.
Pubblicazione: (2025)

On Expressive Power of Quantized Neural Networks under Fixed-Point Arithmetic
di: Park, Yeachan, et al.
Pubblicazione: (2024)

On the Expressive Power of Subgraph Graph Neural Networks for Graphs with Bounded Cycles
di: Chen, Ziang, et al.
Pubblicazione: (2025)

Reducing Smoothness with Expressive Memory Enhanced Hierarchical Graph Neural Networks
di: Bailie, Thomas, et al.
Pubblicazione: (2025)

Topological Expressivity of ReLU Neural Networks
di: Ergen, Ekin, et al.
Pubblicazione: (2023)

Depth-induced NTK: Bridging Over-parameterized Neural Networks and Deep Neural Kernels
di: Tian, Yong-Ming, et al.
Pubblicazione: (2025)

Kernel Correlation-Dissimilarity for Multiple Kernel k-Means Clustering
di: Su, Rina, et al.
Pubblicazione: (2024)

A Theoretical Study of Neural Network Expressive Power via Manifold Topology
di: Yao, Jiachen, et al.
Pubblicazione: (2024)

Learning Expressive Priors for Generalization and Uncertainty Estimation in Neural Networks
di: Schnaus, Dominik, et al.
Pubblicazione: (2023)

On the Expressiveness of Rational ReLU Neural Networks With Bounded Depth
di: Averkov, Gennadiy, et al.
Pubblicazione: (2025)

Expressiveness of Multi-Neuron Convex Relaxations in Neural Network Certification
di: Mao, Yuhao, et al.
Pubblicazione: (2024)

Boosting Graph Neural Network Expressivity with Learnable Lanczos Constraints
di: Azizi, Niloofar, et al.
Pubblicazione: (2024)

NeuronSeek: On Stability and Expressivity of Task-driven Neurons
di: Pei, Hanyu, et al.
Pubblicazione: (2025)

Generalizability of Neural Networks Minimizing Empirical Risk Based on Expressive Ability
di: Yu, Lijia, et al.
Pubblicazione: (2025)

Efficient Private SCO for Heavy-Tailed Data via Averaged Clipping
di: Jin, Chenhan, et al.
Pubblicazione: (2022)

Expressivity of Graph Neural Networks Through the Lens of Adversarial Robustness
di: Campi, Francesco, et al.
Pubblicazione: (2023)

Random Neural Network Expressivity for Non-Linear Partial Differential Equations
di: Mehmood, Muhammed Ali, et al.
Pubblicazione: (2026)