Imagen de Portada

Edge Probability Graph Models Beyond Edge Independency: Concepts, Analyses, and Algorithms

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Bu, Fanchen, Yang, Ruochen, Bogdan, Paul, Shin, Kijung
Formato:	Preprint
Publicado:	2024
Materias:	Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

PyTorch-based Geometric Learning with Non-CUDA Processing Units: Experiences from Intel Gaudi-v2 HPUs
por: Bu, Fanchen, et al.
Publicado: (2025)

On Training-Test (Mis)alignment in Unsupervised Combinatorial Optimization: Observation, Empirical Exploration, and Analysis
por: Bu, Fanchen, et al.
Publicado: (2025)

TiGer: Self-Supervised Purification for Time-evolving Graphs
por: Jo, Hyeonsoo, et al.
Publicado: (2025)

Identifying Group Anchors in Real-World Group Interactions Under Label Scarcity
por: Bu, Fanchen, et al.
Publicado: (2025)

Mitigating Over-Squashing in Graph Neural Networks by Spectrum-Preserving Sparsification
por: Liang, Langzhang, et al.
Publicado: (2025)

DiffIM: Differentiable Influence Minimization with Surrogate Modeling and Continuous Relaxation
por: Lee, Junghun, et al.
Publicado: (2025)

Feature Distribution on Graph Topology Mediates the Effect of Graph Convolution: Homophily Perspective
por: Lee, Soo Yong, et al.
Publicado: (2024)

On Measuring Unnoticeability of Graph Adversarial Attacks: Observations, New Measure, and Applications
por: Jo, Hyeonsoo, et al.
Publicado: (2025)

Tackling Prevalent Conditions in Unsupervised Combinatorial Optimization: Cardinality, Minimum, Covering, and More
por: Bu, Fanchen, et al.
Publicado: (2024)

HyperSearch: Prediction of New Hyperedges through Unconstrained yet Efficient Search
por: Choo, Hyunjin, et al.
Publicado: (2025)

HypeBoy: Generative Self-Supervised Representation Learning on Hypergraphs
por: Kim, Sunwoo, et al.
Publicado: (2024)

Rethinking Reconstruction-based Graph-Level Anomaly Detection: Limitations and a Simple Remedy
por: Kim, Sunwoo, et al.
Publicado: (2024)

SLADE: Detecting Dynamic Anomalies in Edge Streams without Labels via Self-Supervised Learning
por: Lee, Jongha, et al.
Publicado: (2024)

Simple yet Effective Node Property Prediction on Edge Streams under Distribution Shifts
por: Lee, Jongha, et al.
Publicado: (2025)

Spear and Shield: Adversarial Attacks and Defense Methods for Model-Based Link Prediction on Continuous-Time Dynamic Graphs
por: Lee, Dongjin, et al.
Publicado: (2023)

Self-Guided Robust Graph Structure Refinement
por: In, Yeonjun, et al.
Publicado: (2024)

From Raw Features to Effective Embeddings: A Three-Stage Approach for Multimodal Recipe Recommendation
por: Shin, Jeeho, et al.
Publicado: (2025)

Self-Supervised Discovery of Neural Circuits in Spatially Patterned Neural Responses with Graph Neural Networks
por: Yoon, Kijung
Publicado: (2025)

FlowerFormer: Empowering Neural Architecture Encoding using a Flow-aware Graph Transformer
por: Hwang, Dongyeong, et al.
Publicado: (2024)

Learning to Flow from Generative Pretext Tasks for Neural Architecture Encoding
por: Kim, Sunwoo, et al.
Publicado: (2025)

Transfer Learning on Edge Connecting Probability Estimation under Graphon Model
por: Wang, Yuyao, et al.
Publicado: (2025)

ES-GNN: Generalizing Graph Neural Networks Beyond Homophily with Edge Splitting
por: Guo, Jingwei, et al.
Publicado: (2022)

Effective Edge-wise Representation Learning in Edge-Attributed Bipartite Graphs
por: Wang, Hewen, et al.
Publicado: (2024)

Beyond Edge Deletion: A Comprehensive Approach to Counterfactual Explanation in Graph Neural Networks
por: De Sanctis, Matteo, et al.
Publicado: (2026)

A Multimodal Approach to Alzheimer's Diagnosis: Geometric Insights from Cube Copying and Cognitive Assessments
por: Yang, Jaeho, et al.
Publicado: (2025)

Edge-Based Graph Component Pooling
por: Snelleman, T., et al.
Publicado: (2024)

GraphEdge: Dynamic Graph Partition and Task Scheduling for GNNs Computing in Edge Network
por: Xiao, Wenjing, et al.
Publicado: (2025)

Sign is Not a Remedy: Multiset-to-Multiset Message Passing for Learning on Heterophilic Graphs
por: Liang, Langzhang, et al.
Publicado: (2024)

Feature Learning Beyond the Edge of Stability
por: Terjék, Dávid
Publicado: (2025)

Beyond Scaling: Agents Are Heading to the Edge
por: Tian, Chunlin, et al.
Publicado: (2026)

BeGin: Extensive Benchmark Scenarios and An Easy-to-use Framework for Graph Continual Learning
por: Ko, Jihoon, et al.
Publicado: (2022)

EdgeGFL: Rethinking Edge Information in Graph Feature Preference Learning
por: Zhuo, Shengda, et al.
Publicado: (2025)

A Comparative Study of Adaptation Strategies for Time Series Foundation Models in Anomaly Detection
por: Park, Miseon, et al.
Publicado: (2026)

Edge Graph Intelligence: Reciprocally Empowering Edge Networks with Graph Intelligence
por: Zeng, Liekang, et al.
Publicado: (2024)

EdgeMask-DG*: Learning Domain-Invariant Graph Structures via Adversarial Edge Masking
por: Bhattacharya, Rishabh, et al.
Publicado: (2026)

AEGIS: Authentic Edge Growth In Sparsity for Link Prediction in Edge-Sparse Bipartite Knowledge Graphs
por: Liu, Hugh Xuechen, et al.
Publicado: (2025)

Refined Edge Usage of Graph Neural Networks for Edge Prediction
por: Jin, Jiarui, et al.
Publicado: (2022)

RDB2G-Bench: A Comprehensive Benchmark for Automatic Graph Modeling of Relational Databases
por: Choi, Dongwon, et al.
Publicado: (2025)

A Survey on Hypergraph Mining: Patterns, Tools, and Generators
por: Lee, Geon, et al.
Publicado: (2024)

Improved Algorithms for Overlapping and Robust Clustering of Edge-Colored Hypergraphs: An LP-Based Combinatorial Approach
por: Lee, Changyeol, et al.
Publicado: (2025)