Abstract: This specification provides a training method of a hybrid graph neural network model. The hybrid graph neural network model includes an encoding function and a decoding function. The method includes the following: using instances corresponding to all targets in training samples and several nearest neighbors of the instances as nodes in a graph, a graph representation vector of each instance is generated by using the encoding function based on graph data of all the instances. t rounds of training are performed on a decoding parameter; and in each round, bs targets are extracted from training samples, a predicted quantity of each target is generated by using the decoding function based on the graph representation vector of the instance corresponding to each target and non-graph data corresponding to each target, and the decoding parameter is optimized based on a loss quantity of the current round that is determined by the predicted quantities and label quantities of the bs targets in the current round.

Abstract: Disclosed a no-added formaldehyde composite wood product binder, a no-added formaldehyde composite wood product manufactured by same, and a preparation method for the composite wood product. The no-added formaldehyde composite wood product binder comprises an agent A and an agent B. The agent A is an isocyanate-based binder, and the agent B is an aqueous dispersion of polyester based aliphatic polyurethane and/or a modified polyester-based aliphatic polyurethane. The no-added formaldehyde composite wood product is formed under hot-pressing after a wooden and/or straw material is mixed with the no-added formaldehyde composite wood product binder. The composite wood product manufactured by the no-added formaldehyde composite wood product binder has excellent water-proof and mechanical properties and a good saw cutting performance, and the amount of isocyanate used is also reduced, thereby reducing costs.

Abstract: Methods, systems, and apparatus for training a graph neural network. An example method includes obtaining a complete graph; dividing the complete graph into a plurality of subgraphs; obtaining a training graph to participate in graph neural network training based on selecting at least one subgraph from the plurality of subgraphs; obtaining, based on the training graph, a node feature vector of each node in the training graph; obtaining a node fusion vector of each current node in the training graph; determining a loss function based on node labels and the node fusion vectors in the training graph; and iteratively training the graph neural network to update parameter values of the graph neural network based on optimizing the loss function.

Abstract: Methods, systems, and apparatus for training a graph neural network. An example method includes obtaining a complete graph; dividing the complete graph into a plurality of subgraphs; obtaining a training graph to participate in graph neural network training based on selecting at least one subgraph from the plurality of subgraphs; obtaining, based on the training graph, a node feature vector of each node in the training graph; obtaining a node fusion vector of each current node in the training graph; determining a loss function based on node labels and the node fusion vectors in the training graph; and iteratively training the graph neural network to update parameter values of the graph neural network based on optimizing the loss function.

Abstract: Disclosed a no-added formaldehyde composite wood product binder, a no-added formaldehyde composite wood product manufactured by same, and a preparation method for the composite wood product. The no-added formaldehyde composite wood product binder comprises an agent A and an agent B. The agent A is an isocyanate-based binder, and the agent B is an aqueous dispersion of polyester based aliphatic polyurethane and/or a modified polyester-based aliphatic polyurethane. The no-added formaldehyde composite wood product is formed under hot-pressing after a wooden and/or straw material is mixed with the no-added formaldehyde composite wood product binder. The composite wood product manufactured by the no-added formaldehyde composite wood product binder has excellent water-proof and mechanical properties and a good saw cutting performance, and the amount of isocyanate used is also reduced, thereby reducing costs.