Cover Image

Studying and Improving Graph Neural Network-based Motif Estimation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Vieira, Pedro C., Silva, Miguel E. P., Ribeiro, Pedro Manuel Pinto
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

MAGE: Model-Level Graph Neural Networks Explanations via Motif-based Graph Generation
by: Yu, Zhaoning, et al.
Published: (2024)

Impact of Employing Weather Forecast Data as Input to the Estimation of Evapotranspiration by Deep Neural Network Models
by: Vaz, Pedro J., et al.
Published: (2024)

Uncertainty Estimation by Human Perception versus Neural Models
by: Mendes, Pedro, et al.
Published: (2025)

MetaMolGen: A Neural Graph Motif Generation Model for De Novo Molecular Design
by: Yan, Zimo, et al.
Published: (2025)

AMPLE: Event-Driven Accelerator for Mixed-Precision Inference of Graph Neural Networks
by: Gimenes, Pedro, et al.
Published: (2025)

Factor Graph-based Interpretable Neural Networks
by: Li, Yicong, et al.
Published: (2025)

Do Deep Ensembles Actually Capture Uncertainty in Graph Neural Networks?
by: Vieira, Pedro C., et al.
Published: (2026)

Cardinality Estimation over Knowledge Graphs with Embeddings and Graph Neural Networks
by: Schwabe, Tim, et al.
Published: (2023)

Transfer learning in Scalable Graph Neural Network for Improved Physical Simulation
by: Shen, Siqi, et al.
Published: (2025)

Improving Cardiac Risk Prediction Using Data Generation Techniques
by: Cabodevila, Alexandre, et al.
Published: (2025)

LLMTM: Benchmarking and Optimizing LLMs for Temporal Motif Analysis in Dynamic Graphs
by: Hao, Bing, et al.
Published: (2025)

Improving Analog Neural Network Robustness: A Noise-Agnostic Approach with Explainable Regularizations
by: Duque, Alice, et al.
Published: (2024)

CLUE: Neural Networks Calibration via Learning Uncertainty-Error alignment
by: Mendes, Pedro, et al.
Published: (2025)

PowerFlowNet: Power Flow Approximation Using Message Passing Graph Neural Networks
by: Lin, Nan, et al.
Published: (2023)

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

Parallelizing Node-Level Explainability in Graph Neural Networks
by: Llorente, Oscar, et al.
Published: (2026)

Explaining the Explainers in Graph Neural Networks: a Comparative Study
by: Longa, Antonio, et al.
Published: (2022)

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

DeepHGNN: Study of Graph Neural Network based Forecasting Methods for Hierarchically Related Multivariate Time Series
by: Sriramulu, Abishek, 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)

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

Hierarchical Attention-based Graph Neural Network with Relevance-driven Pruning
by: Kum, Seungwoo
Published: (2026)

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

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

Dynamic Graph Structure Estimation for Learning Multivariate Point Process using Spiking Neural Networks
by: Chakraborty, Biswadeep, et al.
Published: (2025)

Spatiotemporal Graph Neural Networks in short term load forecasting: Does adding Graph Structure in Consumption Data Improve Predictions?
by: Nguyen, Quoc Viet, et al.
Published: (2025)

Q-Net: Queue Length Estimation via Kalman-based Neural Networks
by: Gao, Ting, et al.
Published: (2025)

HDNet: Physics-Inspired Neural Network for Flow Estimation based on Helmholtz Decomposition
by: Qi, Miao, et al.
Published: (2024)

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)

Black-box Gradient Attack on Graph Neural Networks: Deeper Insights in Graph-based Attack and Defense
by: Zhan, Haoxi, et al.
Published: (2021)

A Closed-form Solution for Weight Optimization in Fully-connected Feed-forward Neural Networks
by: Tomic, Slavisa, et al.
Published: (2024)

Resource-Aware Neural Network Pruning Using Graph-based Reinforcement Learning
by: Balemans, Dieter, et al.
Published: (2025)

ENADPool: The Edge-Node Attention-based Differentiable Pooling for Graph Neural Networks
by: Zhao, Zhehan, et al.
Published: (2024)

Equivariant Graph Attention Networks with Structural Motifs for Predicting Cell Line-Specific Synergistic Drug Combinations
by: Schwehr, Zachary
Published: (2024)

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)