高维Helmholtz方程柯西问题的磨光化方法

Zhen-ping LI,Yong-sheng ZHANG,Zhi-feng GAO

西北师范大学学报（自然科学版）（2017）

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Abstract

使用磨光化方法研究了固定频率下一类高维Helmholtz方程的柯西问题,该问题是一类解不连续依赖于测量数据的严重不适定的反问题,得到并解决了正则化近似解与精确解之间的收敛性误差估计.

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Key words

ill-posed problem,regularization,Cauchy problem for the Helmholtz equation,mollification method

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Pretraining has recently greatly promoted the development of natural language processing (NLP)
We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance

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