| No belief propagation required: Belief space planning in high-dimensional state spaces via factor graphs, the matrix determinant lemma, and re-use of calculation D Kopitkov, V Indelman The International Journal of Robotics Research 36 (10), 1088-1130, 2017 | 33 | 2017 |
| Neural spectrum alignment: Empirical study D Kopitkov, V Indelman Artificial Neural Networks and Machine Learning–ICANN 2020: 29th …, 2020 | 29 | 2020 |
| General-purpose incremental covariance update and efficient belief space planning via a factor-graph propagation action tree D Kopitkov, V Indelman The International Journal of Robotics Research 38 (14), 1644-1673, 2019 | 16 | 2019 |
| Robot localization through information recovered from cnn classificators D Kopitkov, V Indelman IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems (IROS). IEEE, 2018 | 8 | 2018 |
| Bayesian information recovery from CNN for probabilistic inference D Kopitkov, V Indelman 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2018 | 5 | 2018 |
| Computationally efficient belief space planning via augmented matrix determinant lemma and reuse of calculations D Kopitkov, V Indelman IEEE Robotics and Automation Letters 2 (2), 506-513, 2016 | 3 | 2016 |
| Computationally efficient decision making under uncertainty in high-dimensional state spaces D Kopitkov, V Indelman 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2016 | 3 | 2016 |
| General probabilistic surface optimization and log density estimation D Kopitkov, V Indelman arXiv preprint arXiv:1903.10567, 2019 | 2 | 2019 |
| Deep PDF: Probabilistic surface optimization and density estimation D Kopitkov, V Indelman arXiv preprint arXiv:1807.10728, 2018 | 2 | 2018 |
| Computationally efficient active inference in high-dimensional state spaces D Kopitkov, V Indelman workshop on AI for Long-term Autonomy, in conjunction with the Intl. Conf …, 2016 | 1 | 2016 |
