Cover Image

Geometric Properties and Graph-Based Optimization of Neural Networks: Addressing Non-Linearity, Dimensionality, and Scalability

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Wienczkowski, Michael, Desta, Addisu, Ugochukwu, Paschal
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Linear-Time Graph Neural Networks for Scalable Recommendations
by: Zhang, Jiahao, et al.
Published: (2024)

Graph Neural Networks on Factor Graphs for Robust, Fast, and Scalable Linear State Estimation with PMUs
by: Kundacina, Ognjen, et al.
Published: (2023)

PRES: Toward Scalable Memory-Based Dynamic Graph Neural Networks
by: Su, Junwei, et al.
Published: (2024)

Asynchronous Message Passing for Addressing Oversquashing in Graph Neural Networks
by: Bose, Kushal, et al.
Published: (2025)

Optimizing Sparse Generalized Singular Vectors for Feature Selection in Proximal Support Vector Machines with Application to Breast and Ovarian Cancer Detection
by: Ugwu, Ugochukwu O., et al.
Published: (2024)

Scalable Geometric Learning with Correlation-Based Functional Brain Networks
by: You, Kisung, et al.
Published: (2025)

Random Linear Projections Loss for Hyperplane-Based Optimization in Neural Networks
by: Venkatasubramanian, Shyam, et al.
Published: (2023)

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

Adaptive and AI-Augmented Security Testing: A Systematic Survey of Program Analysis, Feedback-Driven Testing, and Hybrid Learning-Based Approaches
by: Wienczkowski, Michael
Published: (2026)

Graph Neural Networks Uncover Geometric Neural Representations in Reinforcement-Based Motor Learning
by: Nardi, Federico, et al.
Published: (2024)

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

Non-backtracking Graph Neural Networks
by: Park, Seonghyun, et al.
Published: (2023)

Curse of Dimensionality in Neural Network Optimization
by: Na, Sanghoon, et al.
Published: (2025)

Accurate and Scalable Estimation of Epistemic Uncertainty for Graph Neural Networks
by: Trivedi, Puja, et al.
Published: (2024)

GRAPES: Learning to Sample Graphs for Scalable Graph Neural Networks
by: Younesian, Taraneh, et al.
Published: (2023)

Scalable Message Passing Neural Networks: No Need for Attention in Large Graph Representation Learning
by: Borde, Haitz Sáez de Ocáriz, et al.
Published: (2024)

Kernelized Edge Attention: Addressing Semantic Attention Blurring in Temporal Graph Neural Networks
by: Waghmare, Govind, et al.
Published: (2026)

Graph Coarsening via Supervised Granular-Ball for Scalable Graph Neural Network Training
by: Xia, Shuyin, et al.
Published: (2024)

SHAKE-GNN: Scalable Hierarchical Kirchhoff-Forest Graph Neural Network
by: Cui, Zhipu, et al.
Published: (2025)

Non-Intrusive Graph-Based Bot Detection for E-Commerce Using Inductive Graph Neural Networks
by: Zhao, Sichen, et al.
Published: (2026)

Dirac--Bianconi Graph Neural Networks -- Enabling Non-Diffusive Long-Range Graph Predictions
by: Nauck, Christian, et al.
Published: (2024)

Non-convolutional Graph Neural Networks
by: Wang, Yuanqing, et al.
Published: (2024)

Unrolled Graph Neural Networks for Constrained Optimization
by: Hadou, Samar, et al.
Published: (2025)

Torch Geometric Pool: the PyTorch library for pooling in Graph Neural Networks
by: Abate, Carlo, et al.
Published: (2025)

A Survey of Geometric Graph Neural Networks: Data Structures, Models and Applications
by: Han, Jiaqi, et al.
Published: (2024)

Generalization of Geometric Graph Neural Networks with Lipschitz Loss Functions
by: Wang, Zhiyang, et al.
Published: (2024)

Input Snapshots Fusion for Scalable Discrete-Time Dynamic Graph Neural Networks
by: Qi, QingGuo, et al.
Published: (2024)

Accurate and Scalable Graph Neural Networks via Message Invariance
by: Shi, Zhihao, et al.
Published: (2025)

Reproducibility and Geometric Intrinsic Dimensionality: An Investigation on Graph Neural Network Research
by: Hille, Tobias, et al.
Published: (2024)

Scalable Power Control/Beamforming in Heterogeneous Wireless Networks with Graph Neural Networks
by: Zhang, Xiaochen, et al.
Published: (2021)

A Dynamical Systems-Inspired Pruning Strategy for Addressing Oversmoothing in Graph Neural Networks
by: Chakraborty, Biswadeep, et al.
Published: (2024)

Towards Scalable Bayesian Optimization via Gradient-Informed Bayesian Neural Networks
by: Makrygiorgos, Georgios, et al.
Published: (2025)

Scalable Neural Network Training over Distributed Graphs
by: Kolluri, Aashish, et al.
Published: (2023)

Learning to Solve Combinatorial Optimization under Positive Linear Constraints via Non-Autoregressive Neural Networks
by: Wang, Runzhong, et al.
Published: (2024)

TransGAT: Transformer-Based Graph Neural Networks for Multi-Dimensional Automated Essay Scoring
by: Aljuaid, Hind, et al.
Published: (2025)

Non-Euclidean Spatial Graph Neural Network
by: Zhang, Zheng, et al.
Published: (2023)

Causal Explanations from the Geometric Properties of ReLU Neural Networks
by: Woods, Hector, et al.
Published: (2026)

NdLinear: Preserving Multi-Dimensional Structure for Parameter-Efficient Neural Networks
by: Reneau, Alex, et al.
Published: (2025)

Scalable Linearized Laplace Approximation via Surrogate Neural Kernel
by: Ortega, Luis A., et al.
Published: (2026)

Physical Pooling Functions in Graph Neural Networks for Molecular Property Prediction
by: Schweidtmann, Artur M., et al.
Published: (2022)