2 citations · 3 across the 4 of their papers we have counts for
4 papers
CRNNTL: convolutional recurrent neural network and transfer learning for QSAR modelling
Yaqin Li, Yongjin Xu, Yi Yu
In this study, we propose the convolutional recurrent neural network and transfer learning (CRNNTL) for QSAR modelling. The method was inspired by the applications of polyphonic so…
WildWood: a new Random Forest algorithm
Stéphane Gaïffas, Ibrahim Merad, Yiyang Yu
We introduce WildWood (WW), a new ensemble algorithm for supervised learning of Random Forest (RF) type. While standard RF algorithms use bootstrap out-of-bag samples to compute ou…
About contrastive unsupervised representation learning for classification and its convergence
Ibrahim Merad, Yiyang Yu, Emmanuel Bacry +1
Contrastive representation learning has been recently proved to be very efficient for self-supervised training. These methods have been successfully used to train encoders which pe…
ZiMM: a deep learning model for long term and blurry relapses with non-clinical claims data
Anastasiia Kabeshova, Yiyang Yu, Bertrand Lukacs +2
This paper considers the problems of modeling and predicting a long-term and ``blurry'' relapse that occurs after a medical act, such as a surgery. The relapse is observed only ind…