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stein_lib's Introduction

stein_lib

Library for Stein-Variational Gradient Descent methods.

References

[1] Lambert, A.; Hou, B.; Scalise. R.; Srinivasa, S.; Boots, B. (2022). Stein Variational Probabilistic Roadmaps, IEEE/RSJ International Conference on Intelligent Robots and Systems (ICRA).

If you found this code useful, please cite us!

@inproceedings{icra2022_steinprm,
  title={Stein Variational Probabilistic Roadmaps},
  author={Lambert, Alexander and Hou, Brian and Scalise, Rosario and Srinivasa, Siddhartha S and Boots, Byron},
  booktitle={2022 International Conference on Robotics and Automation (ICRA)},
  pages={11094--11101},
  year={2022},
  organization={IEEE}
}

stein_lib's People

Contributors

sashalambert avatar brianhou avatar romesco avatar

Stargazers

avatar avatar Tom Power avatar Xi-Huang avatar avatar An Thai Le avatar Lekan avatar Julen Urain avatar

Watchers

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stein_lib's Issues

Running the tests

I was trying to run the tests but got the following error
`/tests/gaussian_mixture.py", line 145, in
particles, p_hist, pw_dists_sq = svgd.apply(
ValueError: too many values to unpack (expected 3)

`

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