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Interpretable multiattribute collaborative prediction method incorporating domain knowledge and multihead attention mechanism for energetic materials

https://doi.org/10.2139/ssrn.6498666
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Outgoing claims: the papers this work cites, builds on, or argues with.

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QSPR Study for Estimation of Density of Some Aromatic Explosives by Multiple Linear Regression Approach
inferredcites →https://doi.org/10.1002/prep.202400248openalex-snapshot
Multi‐Task Multi‐Fidelity Learning of Properties for Energetic Materials
inferredcites →https://doi.org/10.1007/s41061-023-00435-8openalex-snapshot
Recent Progress on Nitrogen-Rich Energetic Materials Based on Tetrazole Skeleton
inferredcites →https://doi.org/10.1016/j.aichem.2024.100074openalex-snapshot
Conf-GEM: A geometric information-assisted direct conformation generation model
inferredcites →https://doi.org/10.1016/j.apm.2017.07.033openalex-snapshot
Radial basis function approximations: comparison and applications
inferredcites →https://doi.org/10.1016/j.jechem.2024.10.035openalex-snapshot
Machine learning approaches for predicting impact sensitivity and detonation performances of energetic materials
inferredcites →https://doi.org/10.1021/acs.est.4c02421openalex-snapshot
Integrated Transfer Learning and Multitask Learning Strategies to Construct Graph Neural Network Models for Predicting Bioaccumulation Parameters of Chemicals
inferredcites →https://doi.org/10.1021/acs.jcim.2c00841openalex-snapshot
Building Chemical Property Models for Energetic Materials from Small Datasets Using a Transfer Learning Approach
inferredcites →https://doi.org/10.1021/acs.jmedchem.4c02193openalex-snapshot
MPCD: A Multitask Graph Transformer for Molecular Property Prediction by Integrating Common and Domain Knowledge
inferredcites →https://doi.org/10.1021/acsomega.5c07178openalex-snapshot
Efficient Learning of Molecular Properties Using Graph Neural Networks Enhanced with Chemistry Knowledge
inferredcites →https://doi.org/10.1021/ci00057a005openalex-snapshot
SMILES, a chemical language and information system. 1. Introduction to methodology and encoding rules
inferredcites →https://doi.org/10.1038/s41598-018-27344-xopenalex-snapshot
Applying machine learning techniques to predict the properties of energetic materials
inferredcites →https://doi.org/10.1109/tkde.2017.2740926openalex-snapshot
Dependency Analysis of Accuracy Estimates in k-Fold Cross Validation
inferredcites →https://doi.org/10.1109/tnnls.2023.3288769openalex-snapshot
Uncertainty-Adjusted Recommendation via Matrix Factorization With Weighted Losses
inferredcites →https://doi.org/10.1186/1758-2946-5-10openalex-snapshot
InChI in the wild: an assessment of InChIKey searching in Google
inferredcites →https://doi.org/10.1186/s13321-020-00456-1openalex-snapshot
An open source chemical structure curation pipeline using RDKit
inferredcites →https://doi.org/10.1515/9783110442922openalex-snapshot
Energetic Materials Encyclopedia
inferredcites →https://doi.org/10.2174/156802608786786624openalex-snapshot
Medicinal Chemistry and the Molecular Operating Environment (MOE): Application of QSAR and Molecular Docking to Drug Discovery
inferredcites →https://doi.org/10.3390/fi16090318openalex-snapshot
Graph Attention Networks: A Comprehensive Review of Methods and Applications
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