Cover Image

Graph Neural Networks at a Fraction

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Joshi, Rucha Bhalchandra, Barad, Sagar Prakash, Tiwari, Nidhi, Mishra, Subhankar
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

ReconXF: Graph Reconstruction Attack via Public Feature Explanations on Privatized Node Features and Labels
by: Sahoo, Rishi Raj, et al.
Published: (2025)

mHC-GNN: Manifold-Constrained Hyper-Connections for Graph Neural Networks
by: Mishra, Subhankar
Published: (2026)

Estimation of Electronic Band Gap Energy From Material Properties Using Machine Learning
by: Barad, Sagar Prakash, et al.
Published: (2024)

Towards Metric-Faithful Neural Graph Matching
by: Shivottam, Jyotirmaya, et al.
Published: (2026)

Transformers are Graph Neural Networks
by: Joshi, Chaitanya K.
Published: (2025)

Logical Distillation of Graph Neural Networks
by: Pluska, Alexander, et al.
Published: (2024)

Enhancing Neural Theorem Proving through Data Augmentation and Dynamic Sampling Method
by: Vishwakarma, Rahul, et al.
Published: (2023)

QGraphLIME - Explaining Quantum Graph Neural Networks
by: Jena, Haribandhu, et al.
Published: (2025)

Higher-order Spatio-temporal Physics-incorporated Graph Neural Network for Multivariate Time Series Imputation
by: Liang, Guojun, et al.
Published: (2024)

Leveraging Speculative Sampling and KV-Cache Optimizations Together for Generative AI using OpenVINO
by: Barad, Haim, et al.
Published: (2023)

Coupling Graph Neural Networks with Fractional Order Continuous Dynamics: A Robustness Study
by: Kang, Qiyu, et al.
Published: (2024)

NeuroBack: Improving CDCL SAT Solving using Graph Neural Networks
by: Wang, Wenxi, et al.
Published: (2021)

Fine-Grained Graph Generation through Latent Mixture Scheduling
by: Vakil, Nidhi, et al.
Published: (2026)

CFNN: Continued Fraction Neural Network
by: Wang, Chao, et al.
Published: (2026)

QGShap: Quantum Acceleration for Faithful GNN Explanations
by: Jena, Haribandhu, et al.
Published: (2025)

Super Level Sets and Exponential Decay: A Synergistic Approach to Stable Neural Network Training
by: Chaudhary, Jatin, et al.
Published: (2024)

Weakly Supervised Learning on Large Graphs
by: Prakash, Aditya
Published: (2025)

Graphs Unveiled: Graph Neural Networks and Graph Generation
by: Kovács, László, et al.
Published: (2024)

Graph Neural Networks for Learning Equivariant Representations of Neural Networks
by: Kofinas, Miltiadis, et al.
Published: (2024)

Superposition in Graph Neural Networks
by: Pertl, Lukas, et al.
Published: (2025)

Commute Graph Neural Networks
by: Zhuo, Wei, et al.
Published: (2024)

Cooperative Graph Neural Networks
by: Finkelshtein, Ben, et al.
Published: (2023)

Budgeted Attention Allocation: Cost-Conditioned Compute Control for Efficient Transformers
by: Nidhi, Amrit
Published: (2026)

Detecting overfitting in Neural Networks during long-horizon grokking using Random Matrix Theory
by: Prakash, Hari K., et al.
Published: (2026)

GraphXAIN: Narratives to Explain Graph Neural Networks
by: Cedro, Mateusz, et al.
Published: (2024)

Graph Neural Networks Use Graphs When They Shouldn't
by: Bechler-Speicher, Maya, et al.
Published: (2023)

Generalizing Graph Neural Networks on Out-Of-Distribution Graphs
by: Fan, Shaohua, et al.
Published: (2021)

Explaining Graph Neural Networks for Node Similarity on Graphs
by: Daza, Daniel, et al.
Published: (2024)

Prediction of Clinical Complication Onset using Neural Point Processes
by: Weerasekara, Sachini, et al.
Published: (2025)

Spectro-Riemannian Graph Neural Networks
by: Grover, Karish, et al.
Published: (2025)

Causal Graph Neural Networks for Healthcare
by: Mesinovic, Munib, et al.
Published: (2025)

An Active Diffusion Neural Network for Graphs
by: Jiang, Mengying
Published: (2025)

GraphTOP: Graph Topology-Oriented Prompting for Graph Neural Networks
by: Fu, Xingbo, et al.
Published: (2025)

Kolmogorov-Arnold Graph Neural Networks
by: De Carlo, Gianluca, et al.
Published: (2024)

Understanding Pooling in Graph Neural Networks
by: Grattarola, Daniele, et al.
Published: (2021)

Differentiable Cluster Graph Neural Network
by: Dong, Yanfei, et al.
Published: (2024)

Sparse Decomposition of Graph Neural Networks
by: Hu, Yaochen, et al.
Published: (2024)

Continuous Product Graph Neural Networks
by: Einizade, Aref, et al.
Published: (2024)

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

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