Image de couverture de livre

A Metric for the Balance of Information in Graph Learning

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Davies, Alex O., Ajmeri, Nirav S., Filho, Telmo de Menezes e Silva
Format:	Preprint
Publié:	2025
Sujets:	Machine Learning Artificial Intelligence
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Topology Only Pre-Training: Towards Generalised Multi-Domain Graph Models
par: Davies, Alex O., et autres
Publié: (2023)

Language Models Do Not Embed Numbers Continuously
par: Davies, Alex O., et autres
Publié: (2025)

Mind the Gap? A Distributional Comparison of Real and Synthetic Priors for Tabular Foundation Models
par: Davies, Alex O., et autres
Publié: (2026)

Operationalising Rawlsian Ethics for Fairness in Norm-Learning Agents
par: Woodgate, Jessica, et autres
Publié: (2024)

Value-Based Rationales Improve Social Experience: A Multiagent Simulation Study
par: Tzeng, Sz-Ting, et autres
Publié: (2024)

Norm Enforcement with a Soft Touch: Faster Emergence, Happier Agents
par: Tzeng, Sz-Ting, et autres
Publié: (2024)

Time-Series Classification for Dynamic Strategies in Multi-Step Forecasting
par: Green, Riku, et autres
Publié: (2024)

Epistemic Error Decomposition for Multi-step Time Series Forecasting: Rethinking Bias-Variance in Recursive and Direct Strategies
par: Green, Riku, et autres
Publié: (2025)

Stratify: Unifying Multi-Step Forecasting Strategies
par: Green, Riku, et autres
Publié: (2024)

SafeMIL: Learning Offline Safe Imitation Policy from Non-Preferred Trajectories
par: Burnwal, Returaj, et autres
Publié: (2025)

OSIL: Learning Offline Safe Imitation Policies with Safety Inferred from Non-preferred Trajectories
par: Burnwal, Returaj, et autres
Publié: (2026)

Clear Preferences Leave Traces: Reference Model-Guided Sampling for Preference Learning
par: Diwan, Nirav, et autres
Publié: (2025)

Learning from Observation: A Survey of Recent Advances
par: Burnwal, Returaj, et autres
Publié: (2025)

Balancing Graph Embedding Smoothness in Self-Supervised Learning via Information-Theoretic Decomposition
par: Jung, Heesoo, et autres
Publié: (2025)

Balanced Graph Structure Information for Brain Disease Detection
par: Febrinanto, Falih Gozi, et autres
Publié: (2023)

Metric Based Few-Shot Graph Classification
par: Crisostomi, Donato, et autres
Publié: (2022)

Towards Metric-Faithful Neural Graph Matching
par: Shivottam, Jyotirmaya, et autres
Publié: (2026)

Structural Invariance Matters: Rethinking Graph Rewiring through Graph Metrics
par: Benoit, Alexandre, et autres
Publié: (2025)

Metric Learning in an RKHS
par: Tatli, Gokcan, et autres
Publié: (2025)

Metric-DST: Mitigating Selection Bias Through Diversity-Guided Semi-Supervised Metric Learning
par: Tepeli, Yasin I., et autres
Publié: (2024)

Graph Structure Learning with Temporal Graph Information Bottleneck for Inductive Representation Learning
par: Xiong, Jiafeng, et autres
Publié: (2025)

Metric Learning for Clifford Group Equivariant Neural Networks
par: Ali, Riccardo, et autres
Publié: (2024)

An Information Theoretic Evaluation Metric For Strong Unlearning
par: Jeon, Dongjae, et autres
Publié: (2024)

Identifying Backdoored Graphs in Graph Neural Network Training: An Explanation-Based Approach with Novel Metrics
par: Downer, Jane, et autres
Publié: (2024)

Pre-training Graph Neural Networks on Molecules by Using Subgraph-Conditioned Graph Information Bottleneck
par: Hoang, Van Thuy, et autres
Publié: (2024)

Balanced Edge Pruning for Graph Anomaly Detection with Noisy Labels
par: Wang, Zhu, et autres
Publié: (2024)

Federated Learning with Graph-Based Aggregation for Traffic Forecasting
par: Banik, Audri, et autres
Publié: (2025)

A Survey of Imitation Learning Methods, Environments and Metrics
par: Gavenski, Nathan, et autres
Publié: (2024)

Deep Metric Loss for Multimodal Learning
par: Moon, Sehwan, et autres
Publié: (2023)

DPD-Cancer: Explainable Graph-Based Deep Learning for Small Molecule Anti-Cancer Activity Prediction
par: Strømme, Magnus H., et autres
Publié: (2026)

A Distance Metric Learning Model Based On Variational Information Bottleneck
par: Zhang, YaoDan, et autres
Publié: (2024)

BalanceBenchmark: A Survey for Multimodal Imbalance Learning
par: Xu, Shaoxuan, et autres
Publié: (2025)

Dual-Balancing for Multi-Task Learning
par: Lin, Baijiong, et autres
Publié: (2023)

A Riemannian Approach to Ground Metric Learning for Optimal Transport
par: Jawanpuria, Pratik, et autres
Publié: (2024)

GaGSL: Global-augmented Graph Structure Learning via Graph Information Bottleneck
par: Li, Shuangjie, et autres
Publié: (2024)

Learning to Model Graph Structural Information on MLPs via Graph Structure Self-Contrasting
par: Wu, Lirong, et autres
Publié: (2024)

Adaptive Unimodal Regulation for Balanced Multimodal Information Acquisition
par: Huang, Chengxiang, et autres
Publié: (2025)

Adaptive Redundancy Regulation for Balanced Multimodal Information Refinement
par: Yang, Zhe, et autres
Publié: (2025)

A Framework for Selection of Machine Learning Algorithms Based on Performance Metrices and Akaike Information Criteria in Healthcare, Telecommunication, and Marketing Sector
par: Hamisu, A. K., et autres
Publié: (2025)

Surrogate Fitness Metrics for Interpretable Reinforcement Learning
par: Altmann, Philipp, et autres
Publié: (2025)