Saved in:
| Main Author: | Patty, William H |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2509.18161 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Piecewise Constant Spectral Graph Neural Network
by: Martirosyan, Vahan, et al.
Published: (2025)
by: Martirosyan, Vahan, et al.
Published: (2025)
Building Hybrid B-Spline And Neural Network Operators
by: Romagnoli, Raffaele, et al.
Published: (2024)
by: Romagnoli, Raffaele, et al.
Published: (2024)
On the Expressive Power of Transformers for Maxout Networks and Continuous Piecewise Linear Functions
by: Gu, Linyan, et al.
Published: (2026)
by: Gu, Linyan, et al.
Published: (2026)
SmartMixed: A Two-Phase Training Strategy for Adaptive Activation Function Learning in Neural Networks
by: Omidvar, Amin
Published: (2025)
by: Omidvar, Amin
Published: (2025)
Detection Augmented Bandit Procedures for Piecewise Stationary MABs: A Modular Approach
by: Huang, Yu-Han, et al.
Published: (2025)
by: Huang, Yu-Han, et al.
Published: (2025)
Max-Affine Spline Insights Into Deep Network Pruning
by: You, Haoran, et al.
Published: (2021)
by: You, Haoran, et al.
Published: (2021)
Relating Piecewise Linear Kolmogorov Arnold Networks to ReLU Networks
by: Schoots, Nandi, et al.
Published: (2025)
by: Schoots, Nandi, et al.
Published: (2025)
Global Convergence in Neural ODEs: Impact of Activation Functions
by: Gao, Tianxiang, et al.
Published: (2025)
by: Gao, Tianxiang, et al.
Published: (2025)
Ray-Tracing for Conditionally Activated Neural Networks
by: Gallicchio, Claudio, et al.
Published: (2025)
by: Gallicchio, Claudio, et al.
Published: (2025)
Continuity, Piecewise Corrections, and Functor Models in Function-Based Learning
by: Harby, John
Published: (2026)
by: Harby, John
Published: (2026)
Efficient Neural Networks with Discrete Cosine Transform Activations
by: Martinez-Gost, Marc, et al.
Published: (2025)
by: Martinez-Gost, Marc, et al.
Published: (2025)
Learning from Historical Activations in Graph Neural Networks
by: Galron, Yaniv, et al.
Published: (2026)
by: Galron, Yaniv, et al.
Published: (2026)
APEX: Probing Neural Networks via Activation Perturbation
by: Ren, Tao, et al.
Published: (2026)
by: Ren, Tao, et al.
Published: (2026)
Breaking the Conventional Forward-Backward Tie in Neural Networks: Activation Functions
by: Troiano, Luigi, et al.
Published: (2025)
by: Troiano, Luigi, et al.
Published: (2025)
Verification of Geometric Robustness of Neural Networks via Piecewise Linear Approximation and Lipschitz Optimisation
by: Batten, Ben, et al.
Published: (2024)
by: Batten, Ben, et al.
Published: (2024)
LLM Unlearning via Neural Activation Redirection
by: Shen, William F., et al.
Published: (2025)
by: Shen, William F., et al.
Published: (2025)
On the (Non) Injectivity of Piecewise Linear Janossy Pooling
by: Reshef, Ilai, et al.
Published: (2025)
by: Reshef, Ilai, et al.
Published: (2025)
Robust Basis Spline Decoupling for the Compression of Transformer Models
by: De Jonghe, Joppe, et al.
Published: (2026)
by: De Jonghe, Joppe, et al.
Published: (2026)
Z-Error Loss for Training Neural Networks
by: Godin, Guillaume
Published: (2025)
by: Godin, Guillaume
Published: (2025)
Energy Consumption in Parallel Neural Network Training
by: Huber, Philipp, et al.
Published: (2025)
by: Huber, Philipp, et al.
Published: (2025)
Training Neural Networks for Modularity aids Interpretability
by: Golechha, Satvik, et al.
Published: (2024)
by: Golechha, Satvik, et al.
Published: (2024)
Automatic Stability and Recovery for Neural Network Training
by: Or, Barak
Published: (2026)
by: Or, Barak
Published: (2026)
Gradient-Free Training of Quantized Neural Networks
by: Cohen, Noa, et al.
Published: (2024)
by: Cohen, Noa, et al.
Published: (2024)
Steklov Activations: Piecewise-Polynomial Gates with Compact Support and Tunable Sparsity
by: Masalskikh, Aleksandr
Published: (2026)
by: Masalskikh, Aleksandr
Published: (2026)
Probing Graph Neural Network Activation Patterns Through Graph Topology
by: Tori, Floriano, et al.
Published: (2026)
by: Tori, Floriano, et al.
Published: (2026)
ss-Mamba: Semantic-Spline Selective State-Space Model
by: Ye, Zuochen
Published: (2025)
by: Ye, Zuochen
Published: (2025)
Dynamic Spectral Backpropagation for Efficient Neural Network Training
by: Muthuraman, Mannmohan
Published: (2025)
by: Muthuraman, Mannmohan
Published: (2025)
ROOT: Robust Orthogonalized Optimizer for Neural Network Training
by: He, Wei, et al.
Published: (2025)
by: He, Wei, et al.
Published: (2025)
Harnessing Orthogonality to Train Low-Rank Neural Networks
by: Coquelin, Daniel, et al.
Published: (2024)
by: Coquelin, Daniel, et al.
Published: (2024)
Explaining Neural Networks without Access to Training Data
by: Marton, Sascha, et al.
Published: (2022)
by: Marton, Sascha, et al.
Published: (2022)
Piecewise Polynomial Regression of Tame Functions via Integer Programming
by: Bareilles, Gilles, et al.
Published: (2023)
by: Bareilles, Gilles, et al.
Published: (2023)
The Spectral Bias of Shallow Neural Network Learning is Shaped by the Choice of Non-linearity
by: Sahs, Justin, et al.
Published: (2025)
by: Sahs, Justin, et al.
Published: (2025)
On the Rate of Convergence of GD in Non-linear Neural Networks: An Adversarial Robustness Perspective
by: Smorodinsky, Guy, et al.
Published: (2026)
by: Smorodinsky, Guy, et al.
Published: (2026)
Massive Activations in Graph Neural Networks: Decoding Attention for Domain-Dependent Interpretability
by: Bini, Lorenzo, et al.
Published: (2024)
by: Bini, Lorenzo, et al.
Published: (2024)
Emergence of Globally Attracting Fixed Points in Deep Neural Networks With Nonlinear Activations
by: Joudaki, Amir, et al.
Published: (2024)
by: Joudaki, Amir, et al.
Published: (2024)
Mining Generalizable Activation Functions
by: Vitvitskyi, Alex, et al.
Published: (2026)
by: Vitvitskyi, Alex, et al.
Published: (2026)
Toward Improving fNIRS Classification: A Study on Activation Functions in Deep Neural Architectures
by: Adeli, Behtom, et al.
Published: (2025)
by: Adeli, Behtom, et al.
Published: (2025)
Automatic Piecewise Linear Regression for Predicting Student Learning Satisfaction
by: Choi, Haemin, et al.
Published: (2025)
by: Choi, Haemin, et al.
Published: (2025)
Fast Training of Recurrent Neural Networks with Stationary State Feedbacks
by: Caillon, Paul, et al.
Published: (2025)
by: Caillon, Paul, et al.
Published: (2025)
No Prior, No Leakage: Revisiting Reconstruction Attacks in Trained Neural Networks
by: Refael, Yehonatan, et al.
Published: (2025)
by: Refael, Yehonatan, et al.
Published: (2025)
Similar Items
-
Piecewise Constant Spectral Graph Neural Network
by: Martirosyan, Vahan, et al.
Published: (2025) -
Building Hybrid B-Spline And Neural Network Operators
by: Romagnoli, Raffaele, et al.
Published: (2024) -
On the Expressive Power of Transformers for Maxout Networks and Continuous Piecewise Linear Functions
by: Gu, Linyan, et al.
Published: (2026) -
SmartMixed: A Two-Phase Training Strategy for Adaptive Activation Function Learning in Neural Networks
by: Omidvar, Amin
Published: (2025) -
Detection Augmented Bandit Procedures for Piecewise Stationary MABs: A Modular Approach
by: Huang, Yu-Han, et al.
Published: (2025)