Computational Performance of a Germline Variant Calling Pipeline for Next Generation Sequencing

no code implementations • 1 Apr 2020 • Jie Liu, Xiaotian Wu, Kai Zhang, Bing Liu, Renyi Bao, Xiao Chen, Yiran Cai, Yiming Shen, Xinjun He, Jun Yan, Weixing Ji

With the booming of next generation sequencing technology and its implementation in clinical practice and life science research, the need for faster and more efficient data analysis methods becomes pressing in the field of sequencing.

Meta Reinforcement Learning with Distribution of Exploration Parameters Learned by Evolution Strategies

no code implementations • 29 Dec 2018 • Yiming Shen, Kehan Yang, Yufeng Yuan, Simon Cheng Liu

In this paper, we propose a novel meta-learning method in a reinforcement learning setting, based on evolution strategies (ES), exploration in parameter space and deterministic policy gradients.

Meta-Learning Meta Reinforcement Learning +2