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Found 4 papers, 1 papers with code
Batch-Mix Negative Sampling for Learning Recommendation Retrievers
Recommendation retrievers commonly retrieve user potentially preferred items from numerous items, where the query and item representation are learned according to the dual encoders with the log-softmax loss.
Prediction of superconducting properties of materials based on machine learning models
Based on this, this manuscript proposes the use of XGBoost model to identify superconductors; the first application of deep forest model to predict the critical temperature of superconductors; the first application of deep forest to predict the band gap of materials; and application of a new sub-network model to predict the Fermi energy level of materials.
Prediction of properties of metal alloy materials based on machine learning
The experimental results show that the machine learning can predict the material properties accurately.
Molecular distance matrix prediction based on graph convolutional networks
In order to indicate the effect of DMGCN model, the model is compared with the model DeeperGCN-DAGNN and the method of calculating molecular conformation in RDKit.
