Imagen de Portada

Understanding the Design Principles of Link Prediction in Directed Settings

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Zhai, Jun, Ozmen, Muberra, Markovich, Thomas
Formato:	Preprint
Publicado:	2025
Materias:	Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Uncertainty Estimation on Graphs with Structure Informed Stochastic Partial Differential Equations
por: Xu, Fred, et al.
Publicado: (2025)

Score-based change point detection via tracking the best of infinitely many experts
por: Markovich, Anna, et al.
Publicado: (2024)

Understanding Generalization in Node and Link Prediction
por: Vasileiou, Antonis, et al.
Publicado: (2025)

Rethinking Link Prediction for Directed Graphs
por: He, Mingguo, et al.
Publicado: (2025)

Scaling Laws for Discriminative Classification in Large Language Models
por: Wyatte, Dean, et al.
Publicado: (2024)

When to retrain a machine learning model
por: Florence, Regol, et al.
Publicado: (2025)

Is the Frequency Principle always valid?
por: Zhai, Qijia
Publicado: (2025)

Implicit score matching meets denoising score matching: improved rates of convergence and log-density Hessian estimation
por: Yakovlev, Konstantin, et al.
Publicado: (2025)

Multi-Class and Multi-Task Strategies for Neural Directed Link Prediction
por: Moroni, Claudio, et al.
Publicado: (2024)

Direct Prediction Set Minimization via Bilevel Conformal Classifier Training
por: Shi, Yuanjie, et al.
Publicado: (2025)

Automatic mixed precision for optimizing gained time with constrained loss mean-squared-error based on model partition to sequential sub-graphs
por: Markovich-Golan, Shmulik, et al.
Publicado: (2025)

Interpretability as Alignment: Making Internal Understanding a Design Principle
por: Sengupta, Aadit, et al.
Publicado: (2025)

Directed Link Prediction using GNN with Local and Global Feature Fusion
por: Zhang, Yuyang, et al.
Publicado: (2025)

GravityGraphSAGE: Link Prediction in Directed Attributed Graphs
por: Porcedda, Riccardo, et al.
Publicado: (2026)

Directed Criteria Citation Recommendation and Ranking Through Link Prediction
por: Watson, William, et al.
Publicado: (2024)

Parameter Averaging in Link Prediction
por: Sapkota, Rupesh, et al.
Publicado: (2025)

Efficient Low-Rank Matrix Estimation, Experimental Design, and Arm-Set-Dependent Low-Rank Bandits
por: Jang, Kyoungseok, et al.
Publicado: (2024)

Volume Optimality in Conformal Prediction with Structured Prediction Sets
por: Gao, Chao, et al.
Publicado: (2025)

Decision-Focused Sequential Experimental Design: A Directional Uncertainty-Guided Approach
por: Wan, Beichen, et al.
Publicado: (2026)

Bayesian Design Principles for Offline-to-Online Reinforcement Learning
por: Hu, Hao, et al.
Publicado: (2024)

Mind the Links: Cross-Layer Attention for Link Prediction in Multiplex Networks
por: Sharma, Devesh, et al.
Publicado: (2025)

LinkGPT: Teaching Large Language Models To Predict Missing Links
por: He, Zhongmou, et al.
Publicado: (2024)

Resolving Predictive Multiplicity for the Rashomon Set
por: Haghighat, Parian, et al.
Publicado: (2026)

Predictive Churn with the Set of Good Models
por: Watson-Daniels, Jamelle, et al.
Publicado: (2024)

On the Expected Size of Conformal Prediction Sets
por: Dhillon, Guneet S., et al.
Publicado: (2023)

Learning Transferable Friction Models and LuGre Identification Via Physics-Informed Neural Networks
por: Ozmen, Asutay, et al.
Publicado: (2025)

On Design Principles for Private Adaptive Optimizers
por: Ganesh, Arun, et al.
Publicado: (2025)

BoKDiff: Best-of-K Diffusion Alignment for Target-Specific 3D Molecule Generation
por: Yalabadi, Ali Khodabandeh, et al.
Publicado: (2025)

DroughtSet: Understanding Drought Through Spatial-Temporal Learning
por: Tan, Xuwei, et al.
Publicado: (2024)

Quantum LEGO Learning: A Modular Design Principle for Hybrid Artificial Intelligence
por: Qi, Jun, et al.
Publicado: (2026)

Out-of-Distribution Detection for Continual Learning: Design Principles and Benchmarking
por: Gupta, Srishti, et al.
Publicado: (2025)

A Principled Loss Function for Direct Language Model Alignment
por: Tan, Yuandong
Publicado: (2025)

Understanding the Impact of Sampling Quality in Direct Preference Optimization
por: Kim, Kyung Rok, et al.
Publicado: (2025)

Stress Predictions in Polycrystal Plasticity using Graph Neural Networks with Subgraph Training
por: Zhai, Hanfeng
Publicado: (2024)

Future Link Prediction Without Memory or Aggregation
por: Yi, Lu, et al.
Publicado: (2025)

Promoting Fairness in Link Prediction with Graph Enhancement
por: Liu, Yezi, et al.
Publicado: (2024)

LPFormer: An Adaptive Graph Transformer for Link Prediction
por: Shomer, Harry, et al.
Publicado: (2023)

Embedding Learning on Multiplex Networks for Link Prediction
por: Trautmann, Orell, et al.
Publicado: (2026)

Adaptive Set-Mass Calibration with Conformal Prediction
por: Kazantsev, Daniil, et al.
Publicado: (2025)

Set Valued Predictions For Robust Domain Generalization
por: Tsibulsky, Ron, et al.
Publicado: (2025)