1. This paper just simply combines neural networks into the physical sciences problems for predicting TDDFT for molecules. Due to the lack of comparison with other learning based methods and insufficient experiment results, I don’t see the novelty and effectiveness of this method from the learning perspective. Maybe this work is more appropriate for some physical science journals.
2. This paper only does experiments on a very limited number of molecules and only provides in-distribution testing for these samples. I think the value of this method would be limited if it needs to train for each molecule individually.
3. There is no comparison for this method with other state-of-art work but I think using neural networks to predict for molecules is a very popular topic.
2. This paper only does experiments on a very limited number of molecules and only provides in-distribution testing for these samples. I think the value of this method would be limited if it needs to train for each molecule individually.