A Transfer Framework for Enhancing Temporal Graph Learning in Data-Scarce Settings
Fuente:
arXiv
Saved in:
| Main Authors: | Agarwal, Sidharth, Dubey, Tanishq, Gupta, Shubham, Bedathur, Srikanta |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Robust Training of Temporal GNNs using Nearest Neighbours based Hard Negatives
by: Gupta, Shubham, et al.
Published: (2024)
by: Gupta, Shubham, et al.
Published: (2024)
CGLE: Class-label Graph Link Estimator for Link Prediction
by: Mazumder, Ankit, et al.
Published: (2025)
by: Mazumder, Ankit, et al.
Published: (2025)
Can the Rookies Cut the Tough Cookie? Exploring the Use of LLMs for SQL Equivalence Checking
by: Singh, Rajat, et al.
Published: (2024)
by: Singh, Rajat, et al.
Published: (2024)
Efficient Graph Understanding with LLMs via Structured Context Injection
by: Waghmare, Govind, et al.
Published: (2025)
by: Waghmare, Govind, et al.
Published: (2025)
Differentiable Adversarial Attacks for Marked Temporal Point Processes
by: Chakraborty, Pritish, et al.
Published: (2025)
by: Chakraborty, Pritish, et al.
Published: (2025)
Kernelized Edge Attention: Addressing Semantic Attention Blurring in Temporal Graph Neural Networks
by: Waghmare, Govind, et al.
Published: (2026)
by: Waghmare, Govind, et al.
Published: (2026)
Matching Rates and Optimal Allocation for Federated Probe-Logit Distillation under Heterogeneous Bandwidth Budgets
by: Dubey, Prasanjit, et al.
Published: (2026)
by: Dubey, Prasanjit, et al.
Published: (2026)
Transfer Entropy in Graph Convolutional Neural Networks
by: Moldovan, Adrian, et al.
Published: (2024)
by: Moldovan, Adrian, et al.
Published: (2024)
Learning Robust Representations for Communications over Noisy Channels
by: Senthil, Sudharsan, et al.
Published: (2024)
by: Senthil, Sudharsan, et al.
Published: (2024)
Answering Multimodal Exclusion Queries with Lightweight Sparse Disentangled Representations
by: J, Prachi, et al.
Published: (2025)
by: J, Prachi, et al.
Published: (2025)
LWM-Temporal: Sparse Spatio-Temporal Attention for Wireless Channel Representation Learning
by: Alikhani, Sadjad, et al.
Published: (2026)
by: Alikhani, Sadjad, et al.
Published: (2026)
Universal Batch Learning Under The Misspecification Setting
by: Vituri, Shlomi, et al.
Published: (2024)
by: Vituri, Shlomi, et al.
Published: (2024)
Learning Robust Representations for Communications over Interference-limited Channels
by: Paul, Shubham, et al.
Published: (2024)
by: Paul, Shubham, et al.
Published: (2024)
On the Generalization for Transfer Learning: An Information-Theoretic Analysis
by: Wu, Xuetong, et al.
Published: (2022)
by: Wu, Xuetong, et al.
Published: (2022)
ZENN: A Thermodynamics-Inspired Computational Framework for Heterogeneous Data-Driven Modeling
by: Wang, Shun, et al.
Published: (2025)
by: Wang, Shun, et al.
Published: (2025)
Dictionary Based Pattern Entropy for Causal Direction Discovery
by: B, Harikrishnan N, et al.
Published: (2026)
by: B, Harikrishnan N, et al.
Published: (2026)
A Unified Probabilistic Framework for Dictionary Learning with Parsimonious Activation
by: Zhao, Zihui, et al.
Published: (2025)
by: Zhao, Zihui, et al.
Published: (2025)
Generalization in Federated Learning: A Conditional Mutual Information Framework
by: Wang, Ziqiao, et al.
Published: (2025)
by: Wang, Ziqiao, et al.
Published: (2025)
Learning Causality for Longitudinal Data
by: Bouchattaoui, Mouad EL
Published: (2025)
by: Bouchattaoui, Mouad EL
Published: (2025)
A Hierarchical Sampling Framework for bounding the Generalization Error of Federated Learning
by: Filatrella, Dario, et al.
Published: (2026)
by: Filatrella, Dario, et al.
Published: (2026)
Incremental Label Distribution Learning with Scalable Graph Convolutional Networks
by: Jia, Ziqi, et al.
Published: (2024)
by: Jia, Ziqi, et al.
Published: (2024)
Learning Regularities from Data using Spiking Functions: A Theory
by: Zhang, Canlin, et al.
Published: (2024)
by: Zhang, Canlin, et al.
Published: (2024)
Information-Theoretic Framework for Understanding Modern Machine-Learning
by: Feder, Meir, et al.
Published: (2025)
by: Feder, Meir, et al.
Published: (2025)
Dual-Mind World Models: A General Framework for Learning in Dynamic Wireless Networks
by: Wang, Lingyi, et al.
Published: (2025)
by: Wang, Lingyi, et al.
Published: (2025)
Providing Differential Privacy for Federated Learning Over Wireless: A Cross-layer Framework
by: Mao, Jiayu, et al.
Published: (2024)
by: Mao, Jiayu, et al.
Published: (2024)
An Information-Theoretic Analysis of Temporal GNNs
by: Farzaneh, Amirmohammad
Published: (2024)
by: Farzaneh, Amirmohammad
Published: (2024)
Application of Deep Learning in Biological Data Compression
by: Zou, Chunyu
Published: (2025)
by: Zou, Chunyu
Published: (2025)
Transformers Provably Learn Directed Acyclic Graphs via Kernel-Guided Mutual Information
by: Cheng, Yuan, et al.
Published: (2025)
by: Cheng, Yuan, et al.
Published: (2025)
Quantum-Enhanced Hybrid Reinforcement Learning Framework for Dynamic Path Planning in Autonomous Systems
by: Tomar, Sahil, et al.
Published: (2025)
by: Tomar, Sahil, et al.
Published: (2025)
Quantifying the Prediction Uncertainty of Machine Learning Models for Individual Data
by: Bibas, Koby
Published: (2024)
by: Bibas, Koby
Published: (2024)
Cyclic Group Projection for Enumerating Quasi-Cyclic Codes Trapping Sets
by: Usatyuk, Vasiliy, et al.
Published: (2024)
by: Usatyuk, Vasiliy, et al.
Published: (2024)
Federated Testing (FedTest): A New Scheme to Enhance Convergence and Mitigate Adversarial Attacks in Federating Learning
by: Ghaleb, Mustafa, et al.
Published: (2025)
by: Ghaleb, Mustafa, et al.
Published: (2025)
A Framework for Searching in Graphs in the Presence of Errors
by: Dereniowski, Dariusz, et al.
Published: (2018)
by: Dereniowski, Dariusz, et al.
Published: (2018)
Dynamic Feature Selection from Variable Feature Sets Using Features of Features
by: Takahashi, Katsumi, et al.
Published: (2025)
by: Takahashi, Katsumi, et al.
Published: (2025)
A Graph Foundation Model for Wireless Resource Allocation
by: Sheng, Yucheng, et al.
Published: (2026)
by: Sheng, Yucheng, et al.
Published: (2026)
Learning in Convolutional Neural Networks Accelerated by Transfer Entropy
by: Moldovan, Adrian, et al.
Published: (2024)
by: Moldovan, Adrian, et al.
Published: (2024)
Generalization Guarantees for Representation Learning via Data-Dependent Gaussian Mixture Priors
by: Sefidgaran, Milad, et al.
Published: (2025)
by: Sefidgaran, Milad, et al.
Published: (2025)
OmniZip: Learning a Unified and Lightweight Lossless Compressor for Multi-Modal Data
by: Zhao, Yan, et al.
Published: (2026)
by: Zhao, Yan, et al.
Published: (2026)
Environment-Aware Transfer Reinforcement Learning for Sustainable Beam Selection
by: Salami, Dariush, et al.
Published: (2025)
by: Salami, Dariush, et al.
Published: (2025)
Advancing Deep Active Learning & Data Subset Selection: Unifying Principles with Information-Theory Intuitions
by: Kirsch, Andreas
Published: (2024)
by: Kirsch, Andreas
Published: (2024)
Similar Items
-
Robust Training of Temporal GNNs using Nearest Neighbours based Hard Negatives
by: Gupta, Shubham, et al.
Published: (2024) -
CGLE: Class-label Graph Link Estimator for Link Prediction
by: Mazumder, Ankit, et al.
Published: (2025) -
Can the Rookies Cut the Tough Cookie? Exploring the Use of LLMs for SQL Equivalence Checking
by: Singh, Rajat, et al.
Published: (2024) -
Efficient Graph Understanding with LLMs via Structured Context Injection
by: Waghmare, Govind, et al.
Published: (2025) -
Differentiable Adversarial Attacks for Marked Temporal Point Processes
by: Chakraborty, Pritish, et al.
Published: (2025)