Copertina

Do graph neural network states contain graph properties?

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Pelletreau-Duris, Tom, van Bakel, Ruud, Cochez, Michael
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

Applying graph neural network to SupplyGraph for supply chain network
di: Han, Kihwan
Pubblicazione: (2024)

Decomposing heterogeneous dynamical systems with graph neural networks
di: Allier, Cédric, et al.
Pubblicazione: (2024)

Robustness questions the interpretability of graph neural networks: what to do?
di: Lukyanov, Kirill, et al.
Pubblicazione: (2025)

sHGCN: Simplified hyperbolic graph convolutional neural networks
di: Arévalo, Pol, et al.
Pubblicazione: (2025)

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

Development of a graph neural network surrogate for travel demand modelling
di: Makarov, Nikita, et al.
Pubblicazione: (2024)

Distill n' Explain: explaining graph neural networks using simple surrogates
di: Pereira, Tamara, et al.
Pubblicazione: (2023)

Temporal Knowledge-Graph Memory in a Partially Observable Environment
di: Kim, Taewoon, et al.
Pubblicazione: (2024)

Short-Term-to-Long-Term Memory Transfer for Knowledge Graphs under Partial Observability
di: Kim, Taewoon, et al.
Pubblicazione: (2026)

Kolmogorov-Arnold graph neural networks for chemically informed prediction tasks on inorganic nanomaterials
di: Volzhin, Nikita, et al.
Pubblicazione: (2025)

Unifying approach to uniform expressivity of graph neural networks
di: Luo, Huan, et al.
Pubblicazione: (2026)

Enhancing material property prediction with ensemble deep graph convolutional networks
di: Rahman, Chowdhury Mohammad Abid, et al.
Pubblicazione: (2024)

Flow reconstruction in time-varying geometries using graph neural networks
di: Danciu, Bogdan A., et al.
Pubblicazione: (2024)

Effective backdoor attack on graph neural networks in link prediction tasks
di: Dai, Jiazhu, et al.
Pubblicazione: (2024)

Community detection robustness of graph neural networks
di: Goel, Jaidev, et al.
Pubblicazione: (2025)

Inductive Entity Representations from Text via Link Prediction
di: Daza, Daniel, et al.
Pubblicazione: (2020)

Inferred global dense residue transition graphs from primary structure sequences enable protein interaction prediction via directed graph convolutional neural networks
di: Ebeid, Islam Akef, et al.
Pubblicazione: (2025)

Towards graph neural networks for provably solving convex optimization problems
di: Qian, Chendi, et al.
Pubblicazione: (2025)

Counting Still Counts: Understanding Neural Complex Query Answering Through Query Relaxation
di: Brunink, Yannick, et al.
Pubblicazione: (2025)

Crystal structure prediction using graph neural combinatorial optimization
di: Gerolymatos, Stavros, et al.
Pubblicazione: (2026)

Flexible SE(2) graph neural networks with applications to PDE surrogates
di: Bånkestad, Maria, et al.
Pubblicazione: (2024)

Do deep neural networks utilize the weight space efficiently?
di: Koyun, Onur Can, et al.
Pubblicazione: (2024)

Active inference and deep generative modeling for cognitive ultrasound
di: van Sloun, Ruud JG
Pubblicazione: (2024)

Multistage non-deterministic classification using secondary concept graphs and graph convolutional networks for high-level feature extraction
di: Kargar, Masoud, et al.
Pubblicazione: (2024)

Fixed-point graph convolutional networks against adversarial attacks
di: Khan, Shakib, et al.
Pubblicazione: (2025)

Sign language recognition from skeletal data using graph and recurrent neural networks
di: Mederos, B., et al.
Pubblicazione: (2025)

Informed along the road: roadway capacity driven graph convolution network for network-wide traffic prediction
di: Bian, Zilin, et al.
Pubblicazione: (2024)

Simmering: Sufficient is better than optimal for training neural networks
di: Babayan, Irina, et al.
Pubblicazione: (2024)

Finite-difference-informed graph network for solving steady-state incompressible flows on block-structured grids
di: Zou, Yiye, et al.
Pubblicazione: (2024)

Be aware of overfitting by hyperparameter optimization!
di: Tetko, Igor V., et al.
Pubblicazione: (2024)

Iterative Amortized Hierarchical VAE
di: Penninga, Simon W., et al.
Pubblicazione: (2026)

Structured Query Construction via Knowledge Graph Embedding
di: Wang, Ruijie, et al.
Pubblicazione: (2019)

QAGCN: Answering Multi-Relation Questions via Single-Step Implicit Reasoning over Knowledge Graphs
di: Wang, Ruijie, et al.
Pubblicazione: (2022)

Explaining Graph Neural Networks for Node Similarity on Graphs
di: Daza, Daniel, et al.
Pubblicazione: (2024)

Interactive Query Answering on Knowledge Graphs with Soft Entity Constraints
di: Daza, Daniel, et al.
Pubblicazione: (2025)

General agents contain world models
di: Richens, Jonathan, et al.
Pubblicazione: (2025)

On permutation-invariant neural networks
di: Kimura, Masanari, et al.
Pubblicazione: (2024)

Sobolev acceleration for neural networks
di: Oh, Jong Kwon, et al.
Pubblicazione: (2025)

Attention mechanisms in neural networks
di: Hays, Hasi
Pubblicazione: (2026)

Feature learning as alignment: a structural property of gradient descent in non-linear neural networks
di: Beaglehole, Daniel, et al.
Pubblicazione: (2024)