Cover Image

A Complete Symmetry Classification of Shallow ReLU Networks

Fuente: arXiv

Saved in:

Bibliographic Details
Main Author:	Ramakrishnan, Pranavkrishnan
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Algebraic Geometry Combinatorics 68T07, 62J02, 62M45
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

In almost all shallow analytic neural network optimization landscapes, efficient minimizers have strongly convex neighborhoods
by: Benning, Felix, et al.
Published: (2025)

Comparison of generalised additive models and neural networks in applications: A systematic review
by: Doohan, Jessica, et al.
Published: (2025)

Hybrid deep additive neural networks
by: Kim, Gyu Min, et al.
Published: (2024)

A Statistical-Modelling Approach to Feedforward Neural Network Model Selection
by: McInerney, Andrew, et al.
Published: (2022)

Robust Fourier Neural Networks
by: Jeong, Halyun, et al.
Published: (2024)

Generalization error bounds for two-layer neural networks with Lipschitz loss function
by: Nguwi, Jiang Yu, et al.
Published: (2026)

The Predictive-Causal Gap: An Impossibility Theorem and Large-Scale Neural Evidence
by: Liu, Kejun
Published: (2026)

Deep Neural Network Based Accelerated Failure Time Models using Rank Loss
by: Kim, Gwangsu, et al.
Published: (2022)

Fractal and Regular Geometry of Deep Neural Networks
by: Di Lillo, Simmaco, et al.
Published: (2025)

A Special Case of Quadratic Extrapolation Under the Neural Tangent Kernel
by: Kim, Abiel
Published: (2025)

ASNN: Learning to Suggest Neural Architectures from Performance Distributions
by: Hong, Jinwook
Published: (2025)

Geometry and Optimization of Shallow Polynomial Networks
by: Arjevani, Yossi, et al.
Published: (2025)

Error analysis for empirical risk minimization over clipped ReLU networks in solving linear Kolmogorov partial differential equations
by: Xiao, Jichang, et al.
Published: (2023)

Operator Learning Using Random Features: A Tool for Scientific Computing
by: Nelsen, Nicholas H., et al.
Published: (2024)

Machine Collaboration
by: Liu, Qingfeng, et al.
Published: (2021)

An Efficient Approach to Regression Problems with Tensor Neural Networks
by: Li, Yongxin, et al.
Published: (2024)

From Theory to Application: A Practical Introduction to Neural Operators in Scientific Computing
by: Jha, Prashant K.
Published: (2025)

Universal Adaptive Environment Discovery
by: Matymov, Madi, et al.
Published: (2025)

Optimizing Data Augmentation through Bayesian Model Selection
by: Matymov, Madi, et al.
Published: (2025)

Beyond Least Squares: Robust Regression Transformer (R2T)
by: Gutierrez, Roman, et al.
Published: (2025)

Deep Neural Networks for Doubly Robust Estimation with Nonprobability Survey Samples
by: Dai, Yufang, et al.
Published: (2026)

SAGA: A Sequence-Adaptive Generative Architecture for Multi-Horizon Probabilistic Forecasting with Adaptive Temporal Conformal Prediction
by: Lundström-Imanov, Gustav Olaf Yunus Laitinen-Fredriksson, et al.
Published: (2026)

Empirical Mode Decomposition and Graph Transformation of the MSCI World Index: A Multiscale Topological Analysis for Graph Neural Network Modeling
by: Riscos, Agustín M. de los, et al.
Published: (2025)

Dirichlet Scale Mixture Priors for Bayesian Neural Networks
by: Arnstad, August, et al.
Published: (2026)

A Geometric Analysis of Sign-Magnitude Asymmetry in a ReLU + RMSNorm Block under Ternary Quantization
by: Dong, Lei
Published: (2026)

Efficient Global Optimization of Two-Layer ReLU Networks: Quadratic-Time Algorithms and Adversarial Training
by: Bai, Yatong, et al.
Published: (2022)

Identifiability of Deep Polynomial Neural Networks
by: Usevich, Konstantin, et al.
Published: (2025)

Mathematical Theory of Collinearity Effects on Machine Learning Variable Importance Measures
by: Bladen, Kelvyn K., et al.
Published: (2025)

Approximation Rates for Shallow ReLU$^k$ Neural Networks on Sobolev Spaces via the Radon Transform
by: Mao, Tong, et al.
Published: (2024)

Mixed Semi-Supervised Generalized-Linear-Regression with Applications to Deep-Learning and Interpolators
by: Yuval, Oren, et al.
Published: (2023)

G-Mapper: Learning a Cover in the Mapper Construction
by: Alvarado, Enrique, et al.
Published: (2023)

Predicting California Bearing Ratio with Ensemble and Neural Network Models: A Case Study from Turkiye
by: Kökçam, Abdullah Hulusi, et al.
Published: (2025)

Polynomial Chaos Surrogate Construction for Random Fields with Parametric Uncertainty
by: Mueller, Joy N., et al.
Published: (2023)

WTNN: Weibull-Tailored Neural Networks for survival analysis
by: Rives, Gabrielle, et al.
Published: (2025)

Distributed Sparse Linear Regression under Communication Constraints
by: Fonseca, Rodney, et al.
Published: (2023)

GT-PCA: Effective and Interpretable Dimensionality Reduction with General Transform-Invariant Principal Component Analysis
by: Heinrichs, Florian
Published: (2024)

Spectral Algorithms under Covariate Shift
by: Fan, Jun, et al.
Published: (2025)

Generalization and Feature Attribution in Machine Learning Models for Crop Yield and Anomaly Prediction in Germany
by: Baatz, Roland
Published: (2025)

Pathological Regularization Regimes in Classification Tasks
by: Wiesmann, Maximilian, et al.
Published: (2024)

Bayesian--AI Fusion for Epidemiological Decision Making: Calibrated Risk, Honest Uncertainty, and Hyperparameter Intelligence
by: Chatterjee, Debashis
Published: (2025)