Copertina

PF-GNN: Differentiable particle filtering based approximation of universal graph representations

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Dupty, Mohammed Haroon, Dong, Yanfei, Lee, Wee Sun
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Machine Learning Artificial Intelligence
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Differentiable Cluster Graph Neural Network
di: Dong, Yanfei, et al.
Pubblicazione: (2024)

Improving Molecular Force Fields with Minimal Temporal Information
di: Mollahosseini, Ali, et al.
Pubblicazione: (2026)

Hierarchical Neural Constructive Solver for Real-world TSP Scenarios
di: Goh, Yong Liang, et al.
Pubblicazione: (2024)

Implicit Graph Neural Diffusion Networks: Convergence, Generalization, and Over-Smoothing
di: Fu, Guoji, et al.
Pubblicazione: (2023)

Constrained Layout Generation with Factor Graphs
di: Dupty, Mohammed Haroon, et al.
Pubblicazione: (2024)

Differentiable Tree Search Network
di: Mittal, Dixant, et al.
Pubblicazione: (2024)

SHIELD: Multi-task Multi-distribution Vehicle Routing Solver with Sparsity and Hierarchy
di: Goh, Yong Liang, et al.
Pubblicazione: (2025)

Tackling Oversmoothing in GNN via Graph Sparsification: A Truss-based Approach
di: Hossain, Tanvir, et al.
Pubblicazione: (2024)

A Differential Geometric View and Explainability of GNN on Evolving Graphs
di: Liu, Yazheng, et al.
Pubblicazione: (2024)

Electrostatics-based particle sampling and approximate inference
di: Huang, Yongchao
Pubblicazione: (2024)

GNN-based Passenger Request Prediction
di: Makhdomi, Aqsa Ashraf, et al.
Pubblicazione: (2023)

Locality Sensitive Sparse Encoding for Learning World Models Online
di: Liu, Zichen, et al.
Pubblicazione: (2024)

On the Empirical Complexity of Reasoning and Planning in LLMs
di: Kang, Liwei, et al.
Pubblicazione: (2024)

LiGNN: Graph Neural Networks at LinkedIn
di: Borisyuk, Fedor, et al.
Pubblicazione: (2024)

Understanding the theoretical properties of projected Bellman equation, linear Q-learning, and approximate value iteration
di: Lim, Han-Dong, et al.
Pubblicazione: (2025)

GNN-based Probabilistic Supply and Inventory Predictions in Supply Chain Networks
di: Ahn, Hyung-il, et al.
Pubblicazione: (2024)

Continual Reinforcement Learning by Planning with Online World Models
di: Liu, Zichen, et al.
Pubblicazione: (2025)

TrustGuard: GNN-based Robust and Explainable Trust Evaluation with Dynamicity Support
di: Wang, Jie, et al.
Pubblicazione: (2023)

Knowledge Graph Sparsification for GNN-based Rare Disease Diagnosis
di: Cara, Premt, et al.
Pubblicazione: (2025)

MASP: Scalable GNN-based Planning for Multi-Agent Navigation
di: Yang, Xinyi, et al.
Pubblicazione: (2023)

Understanding Expressivity of GNN in Rule Learning
di: Qiu, Haiquan, et al.
Pubblicazione: (2023)

An Empirical Study of Realized GNN Expressiveness
di: Wang, Yanbo, et al.
Pubblicazione: (2023)

Extending Epistemic Uncertainty Beyond Parameters Would Assist in Designing Reliable LLMs
di: Nguyen-Hien, T. Duy, et al.
Pubblicazione: (2025)

SofT-GRPO: Surpassing Discrete-Token LLM Reinforcement Learning via Gumbel-Reparameterized Soft-Thinking Policy Optimization
di: Zheng, Zhi, et al.
Pubblicazione: (2025)

Toward a universal foundation model for graph-structured data
di: Mostafa, Sakib, et al.
Pubblicazione: (2026)

Target Circuit Matching in Large-Scale Netlists using GNN-Based Region Prediction
di: Seo, Sangwoo, et al.
Pubblicazione: (2025)

GNN's Uncertainty Quantification using Self-Distillation
di: Daneshvar, Hirad, et al.
Pubblicazione: (2025)

Forget and Explain: Transparent Verification of GNN Unlearning
di: Ahsan, Imran, et al.
Pubblicazione: (2025)

FLAG: Financial Long Document Classification via AMR-based GNN
di: Xia, Bolun "Namir", et al.
Pubblicazione: (2024)

Advanced atom-level representations for protein flexibility prediction utilizing graph neural networks
di: Sarparast, Sina, et al.
Pubblicazione: (2024)

GNN-as-Judge: Unleashing the Power of LLMs for Graph Learning with GNN Feedback
di: Xu, Ruiyao, et al.
Pubblicazione: (2026)

DECODE: Data-driven Energy Consumption Prediction leveraging Historical Data and Environmental Factors in Buildings
di: Mishra, Aditya, et al.
Pubblicazione: (2023)

FedPF: Accurate Target Privacy Preserving Federated Learning Balancing Fairness and Utility
di: Sun, Kangkang, et al.
Pubblicazione: (2025)

GNN Explanations that do not Explain and How to find Them
di: Azzolin, Steve, et al.
Pubblicazione: (2026)

Shapley-Value-Based Graph Sparsification for GNN Inference
di: Akkas, Selahattin, et al.
Pubblicazione: (2025)

BHyGNN+: Unsupervised Representation Learning for Heterophilic Hypergraphs
di: Ma, Tianyi, et al.
Pubblicazione: (2026)

Improving out-of-distribution generalization in graphs via hierarchical semantic environments
di: Piao, Yinhua, et al.
Pubblicazione: (2024)

StormNet: Improving storm surge predictions with a GNN-based spatio-temporal offset forecasting model
di: Nader, Noujoud, et al.
Pubblicazione: (2026)

MQ-GNN: A Multi-Queue Pipelined Architecture for Scalable and Efficient GNN Training
di: Ullah, Irfan, et al.
Pubblicazione: (2026)

LLM and GNN are Complementary: Distilling LLM for Multimodal Graph Learning
di: Xu, Junjie, et al.
Pubblicazione: (2024)