报告人：张欣博士
报告题目：Variational Geophysical Inversion
摘要：Bayesian inference has become a valuable tool to solve geophysical inverse problems. However, the commonly-used Markov chain Monte Carlo (McMC) methods are generally computationally intractable for large datasets and high-dimensional parameter spaces. In this talk, I introduce a new method called variational inference to solve geophysical inverse problems. Variational inference uses optimization to solve the inverse problem, yet still produces fully nonlinear, probabilistic results. By applying the method to a range of applications, including travel time tomography and full waveform inversion, I demonstrate that variational inference can produce accurate approximations to the results obtained using McMC with significantly reduced computational cost. The method therefore provides an efficient alternative to McMC methods and can be applied to a variety of geophysical inverse problems.
报告时间：2022年9月9日周五下午16:00-17:00
报告形式：腾讯会议193-330-854
报告人简介：张欣，英国爱丁堡大学地球科学学院博士后研究员。2012年和2015年分别获得中国科学技术大学学士和硕士学位。2020年获得英国爱丁堡大学地球物理学博士学位，并继续从事博士后研究至今。主要研究方向包括贝叶斯地球物理反演、机器学习地球物理反演、地震层析成像以及全波形反演等。他在Journal of Geophysical Research、Geophysical Journal International、Advances in Geophysics等杂发表了二十多篇相关研究的论文，研究成果被广泛应用于学术界和工业界。
