Büchler, Dieter Dept. Empirical Inference, Max Planck Institute for Intelligent Systems, Max Planck Society;
https://corlconf.github.io/corl2020/paper_159 (Any fulltext)
https://doi.org/10.48550/arXiv.2010.10201 (Preprint)
https://proceedings.mlr.press/v155/shaj21a.html (Publisher version)
https://youtu.be/fNHtSqLYLFs (Multimedia)
Shaj, V., Becker, P., Büchler, D., Pandya, H., van Duijkeren, N., Taylor, C. J., et al. (2020). Action-Conditional Recurrent Kalman Networks For Forward and Inverse Dynamics Learning. In J. Kober, F. Ramos, & C. Tomlin (Eds.), Proceedings of the 2020 Conference on Robot Learning (CoRL 2020) (pp. 765-781). PMLR. Retrieved from https://proceedings.mlr.press/v155/shaj21a.html.
