Yasunaga M, Liang P (2020) Graph-based, self-supervised program repair from diagnostic feedback. In: International conference on machine learning, PMLR, pp 10799–10808 You Y, Chen T, Sui Y, Chen T, Wang Z, Shen Y (2020a) Graph contrastive learning with augmentations. Adv Neural Inf Pr...
15 Dec 2021·Arman Hasanzadeh,Mohammadreza Armandpour,Ehsan Hajiramezanali,Mingyuan Zhou,Nick Duffield,Krishna Narayanan· Contrastive learning has become a key component of self-supervised learning approaches for graph-structured data. Despite their success, existing graph contrastive learning methods are ...
Mechanic EngineeringBao, X., Chen, L., Zhong, J., Wu, D. and Zheng, Y., 2024. A self-supervised contrastive change point detection method for industrial time series. Engineering Applications of Artificial Intelligence, 133, p.108217. ...
PCNet-M utilizes Mask RCNN [15] as an instance seg- mentation backbone and learns amodal completion by arti- ficially occluding objects with other objects from the same dataset in a self-supervised manner. Hence, PCNet-M is considered to ...
2.1. Reinforcement Learning RL is one of the three learning paradigms in ML next to Supervised and Unsupervised Learning. In RL, there is an agent, which is the learner and decision-maker: it has to understand how to use the information of the environment to choose the best action. Everyth...