# Graph neural network

### Graph Neural Network for Minimum Dominating Set

**graph**is either in D or adjacent to a vertex in D. In a

**graph**on n nodes if there is a single node of degree n-1 then that single node forms a minimum dominating ...designed

**network**called ...

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### Text Level Graph Neural Network for Text Classification

**graph**

**neural**

**network**(GNN) techniques on text clas- sification, since GNN does well in handling complex structures and preserving global in- ...level

**graph**structure which do not support ...

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### A Lexicon Based Graph Neural Network for Chinese NER

**neural**networks (RNN) used for Chinese named entity recognition (NER) that sequentially track character and word infor- mation have achieved great ...lexicon-based

**graph**

**neural**...

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### Multi Channel Graph Neural Network for Entity Alignment

**Graph**

**Neural**

**Network**model, MuGNN, which learns alignment-oriented KG embeddings for en- tity ...robust

**graph**encoding ...

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### Learning to Solve NP-Complete Problems: A Graph Neural Network for Decision TSP

**Graph**

**Neural**Networks (GNN) are a promising technique for bridging differential programming and combinatorial ...a

**network**can be trained with sets of dual examples: given the optimal tour cost C ∗ , ...

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### Subgraph Matching Using Graph Neural Network

**graph**matching problems and have compared with greedy algorithm approach on

**graph**matching ...sub-

**graph**isomorphism problem in planar graphs in linear time, for any pattern of constant size ...

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### Attributed Graph Classification via Deep Graph Convolutional Neural Networks

**Graph**Convolutional

**Neural**Networks (GCNs) are a class of

**neural**networks, explicitly designed for in-depth analysis of

**graph**-structured data (Bruna et ...by

**graph**signal ...

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### AutoNet: Knowledge Graphs for Occasions Object Recognition

**Graph**Choose Search

**Neural**

**Network**(GG-CSNN) for learning

**Graph**

**Neural**...the

**graph**

**network**as our initial set of active entities ...

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### Representing Schema Structure with Graph Neural Networks for Text to SQL Parsing

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### Graph convolutional networks: a comprehensive review

**graph**convolutional models become ...two-layer

**graph**convolution model often achieves the best performance in GCN [37] and GraphSAGE ...the

**graph**convolutional models deeper, by borrowing the ...

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### A Novel Neural Network Model for Joint POS Tagging and Graph based Dependency Parsing

**graph**- or transition-based parsing ap- proaches manually define a set of core and com- bined features associated with one-hot representa- tions (McDonald and Pereira, 2006; Nivre et ...to

**neural**...

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### The Application of BP Neural Network in Leukocyte Classification Recognition

**neural**

**network**is the most widely used and most mature technology in artificial intelligence information fusion; classification recognition is one of the main ...BP

**neural**

**network**...

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### DEVELOPING A NEURO-GENETIC MODEL TO EFFECTIVELY PREDICT STOCK PRICES IN BSE SENSEX, 2018

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### Speech Enhancement Using Neural Network

**network**architecture with minimum ...(MLP)

**network**and trained using the backpropagation algorithm (BPA).

**Neural**

**network**have existed for a long time and have recently enjoyed a ...

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### Transition based Dependency Parsing Using Two Heterogeneous Gated Recursive Neural Networks

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### Two-phase multi-model automatic brain tumour diagnosis system from magnetic resonance images using convolutional neural networks

**neural**net- work (FCNN) and conditional random fields (CRFs) as a post-processing step to segment brain tumours with an obtained DICE score of ...convolutional

**network**(FCN) with ...

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### Short Term Load Forecasting With Feed Forward Neural Network Algorithm

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### Intelligent monitoring of a complex, non-linear system using artificial neural networks

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### Graph based Dependency Parsing with Graph Neural Networks

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### Cholesky ANN models for predicting multivariate realized volatility

**Neural**Networks specification here pre- sented provides a twofold advantage for this ...artificial

**neural**networks allows to specify nonlin- ear relations without any particular ...

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