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Found 3 papers, 2 papers with code
Country-level Arabic Dialect Identification using RNNs with and without Linguistic Features
This work investigates the value of augmenting recurrent neural networks with feature engineering for the Second Nuanced Arabic Dialect Identification (NADI) Subtask 1. 2: Country-level DA identification.
Transfer Learning Using Ensemble Neural Networks for Organic Solar Cell Screening
In this work, we present an ensemble deep neural network architecture, called SINet, which harnesses both the SMILES and InChI molecular representations to predict HOMO values and leverage the potential of transfer learning from a sizeable DFT-computed dataset- Harvard CEP to build more robust predictive models for relatively smaller HOPV datasets.
CheMixNet: Mixed DNN Architectures for Predicting Chemical Properties using Multiple Molecular Representations
SMILES is a linear representation of chemical structures which encodes the connection table, and the stereochemistry of a molecule as a line of text with a grammar structure denoting atoms, bonds, rings and chains, and this information can be used to predict chemical properties.
