1887
PDF

Abstract

Summary

Not Provided

Loading

Article metrics loading...

/content/papers/10.3997/2214-4609.202379012
2023-11-21
2025-04-18
Loading full text...

Full text loading...

/deliver/fulltext/2214-4609/2023/2nd-eage-workshop-on-quantifying-uncertainty-in-depth-imaging/12_-_Zhang-Xin.html?itemId=/content/papers/10.3997/2214-4609.202379012&mimeType=html&fmt=ahah

References

  1. Liu, Q. & Wang, D., 2016. Stein variational gradient descent: a general purpose Bayesian inference algorithm, in Advances In Neural Information Processing Systems, pp. 2378–2386.
    [Google Scholar]
  2. Ma, Y.-A., Chen, T. & Fox, E., 2015. A complete recipe for stochastic gradient MCMC, in NIPS’15: Proceedings of the 28th International Conference on Neural Information Processing Systems, Vol. 2, pp. 2917–2925, MIT Press.
    [Google Scholar]
  3. Zhang, X. & Curtis, A., 2020. Seismic tomography using variational inference methods, J. geophys. Res., 125(4), e2019JB018589.
    [Google Scholar]
  4. Zhang, X., Lomas, A., Zhou, M., Zheng, Y., & Curtis, A., 2023. 3-D Bayesian variational full waveform inversion, Geophysical Journal International, 234(1), 546–561.
    [Google Scholar]
/content/papers/10.3997/2214-4609.202379012
Loading
/content/papers/10.3997/2214-4609.202379012
Loading

Data & Media loading...

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error