… This paper presents a PHM model which combines multiple deep learning algorithms for
condition assessment, fault classification, sensor prediction, and remaining useful life (RUL) …

… INTRODUCTION DEEP learning (DL) has gained great … “Deep learning in physical layer
communications.” [Online]. … Juang, “Power of deep learning for channel estimation and signal …

… and prioritize effective drug combinations are important for combination therapy discovery. …
deep learning model, AuDNNsynergy, to predict the synergy of pairwise drug combinations …

… learning algorithms and deep learning are applied to compare the results and analysis of
the UCI Machine Learning … Using deep learning approach, 94.2% accuracy was obtained. …

… In comparison, DNNLOC is a combination between ML and IR. We use deep learning to
learn the connections between the terms in bug reports and source files. Their approach with …

… phenomena of traditional combination methods and to improve prediction performance, this
paper proposes an improved Bayesian combination model with deep learning (IBCM-DL) for …

… the hyperspectral image, we try to find an optimal feature combination for each class, which
is the building block of deep learning. Therefore, an LR classifier was chosen to predict the …

… a deep learning architecture, which we call ComboNet, that jointly models molecular structure,
as well as biological targets, for the purpose of predicting synergistic drug combinations. …

… • A novel deep learning combination method that automatically selects strong modalities
per sample and ignores weak modalities is proposed and experimentally evaluated. The …

… Systems combining deep learning and reinforcement learning are in their infancy, but they
already outperform passive vision systems 99 at classification tasks and produce impressive …