… on the reliability of scoring functions (SFs). With the rapid development of machine learning
(ML) … Emergence of more data-hungry deep learning (DL) approaches in recent years further …

… than classical scoring functions when applied within their applicability domain. Here we
review structure-based scoring functions for binding affinity prediction based on deep learning, …

… In this work, we proposed a deep learning–based model named … deeper integration of
deep learning and chemical informatics, we believe that deep learning–based scoring functions …

… The recently reported machine learning- or deep learning-based scoring functions (SFs)
have shown exciting performance in predicting protein–ligand binding affinities with fruitful …

… for multivariate scoring functions, in which the relevance score of a … to this framework as
GSFs—groupwise scoring functions. We … of learning-to-rank research using deep learning. …

… Then, we present a deep learning architecture to predict a grasp quality score from a depth
… a suboptimal gripper pose to have a higher score. For grasp prediction, the learned network …

… Here, we propose a virtual screening method based on deep learning, called Deep Scoring,
which directly extracts the relative position information and atomic attribute information on …

… Deep Learning (DL) Compared with the scoring functions discussed above, the DL scoring
function … is one of the common deep learning models for scoring functions. This model can be …

… in the credit scoring literature. The main motivation for this research is to consider the
appropriateness of deep learning algorithms for credit scoring. To this end two deep learning …

… A panel of 25 scoring functions are tested on CASF-2016 as a demonstration. Our results …
of current scoring functions is more promising in terms of docking power than scoring, ranking, …