X Gao, S Jin, CK Wen, GY Li - IEEE Communications Letters, 2018 - ieeexplore.ieee.org
… INTRODUCTION DEEPlearning (DL) has gained great … “Deeplearning in physical layer communications.” [Online]. … Juang, “Power of deeplearning for channel estimation and signal …
T Zhang, L Zhang, PRO Payne, F Li - Translational bioinformatics for …, 2021 - Springer
… and prioritize effective drug combinations are important for combination therapy discovery. … deeplearning model, AuDNNsynergy, to predict the synergy of pairwise drug combinations …
… learning algorithms and deeplearning are applied to compare the results and analysis of the UCI Machine Learning … Using deeplearning approach, 94.2% accuracy was obtained. …
… In comparison, DNNLOC is a combination between ML and IR. We use deeplearning to learn the connections between the terms in bug reports and source files. Their approach with …
Y Gu, W Lu, X Xu, L Qin, Z Shao… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
… phenomena of traditional combination methods and to improve prediction performance, this paper proposes an improved Bayesian combination model with deeplearning (IBCM-DL) for …
W Zhao, Z Guo, J Yue, X Zhang… - International Journal of …, 2015 - Taylor & Francis
… the hyperspectral image, we try to find an optimal feature combination for each class, which is the building block of deeplearning. Therefore, an LR classifier was chosen to predict the …
… a deeplearning 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 deeplearningcombination method that automatically selects strong modalities per sample and ignores weak modalities is proposed and experimentally evaluated. The …
… Systems combiningdeeplearning and reinforcement learning are in their infancy, but they already outperform passive vision systems 99 at classification tasks and produce impressive …