Dmitry Kopitkov

Ph.D.

2020

Meta

Ph.D. TASP, Technion, 2020

M.Sc. Summa Cum Laude, TASP, Technion, 2017

B.Sc. Magna Cum Laude, CS, Academic College of Tel Aviv-Yaffo, 2012

ANPL Publications:

  1. D. Kopitkov and V. Indelman, “Neural Spectrum Alignment: Empirical Study,” in International Conference on Artificial Neural Networks (ICANN), Sep. 2020.
    Kopitkov20icann.pdf Kopitkov20icann.supplementary
  2. D. Kopitkov, “General Probabilistic Surface Optimization and Log Density Estimation,” PhD thesis, Technion - Israel Institute of Technology, 2020.
    Kopitkov20thesis.pdf Kopitkov20thesis.slides Kopitkov20thesis.video
  3. D. Kopitkov and V. Indelman, “General Probabilistic Surface Optimization and Log Density Estimation,” 2019.
    arXiv: https://arxiv.org/pdf/1903.10567
  4. D. Kopitkov and V. Indelman, “General Purpose Incremental Covariance Update and Efficient Belief Space Planning via Factor-Graph Propagation Action Tree,” 2019.
    arXiv: https://arxiv.org/abs/1906.02249
  5. D. Kopitkov and V. Indelman, “General Purpose Incremental Covariance Update and Efficient Belief Space Planning via Factor-Graph Propagation Action Tree,” International Journal of Robotics Research (IJRR), no. 14, Sep. 2019.
    Kopitkov19ijrr.pdf URL: https://journals.sagepub.com/doi/10.1177/0278364919875199
  6. D. Kopitkov and V. Indelman, “Neural Spectrum and Gradient Similarity,” in DeepMath - Conference on the Mathematical Theory of Deep Neural Networks, Nov. 2019.
    Kopitkov19deepmath.poster
  7. D. Kopitkov and V. Indelman, “Bayesian Information Recovery from CNN for Probabilistic Inference,” in IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Oct. 2018.
    Kopitkov18iros.pdf Kopitkov18iros.slides
  8. D. Kopitkov and V. Indelman, “Deep PDF: Probabilistic Surface Optimization and Density Estimation,” 2018.
    arXiv: http://arxiv.org/abs/1807.10728
  9. D. Kopitkov and V. Indelman, “Computationally Efficient Belief Space Planning via Augmented Matrix Determinant Lemma and Re-Use of Calculations,” IEEE Robotics and Automation Letters (RA-L), no. 2, 2017.
    Kopitkov17ral.pdf Kopitkov17ral.slides URL: http://ieeexplore.ieee.org/document/7801141/ Kopitkov17ral.supplementary
  10. D. Kopitkov and V. Indelman, “No Belief Propagation Required: Belief Space Planning in High-Dimensional State Spaces via Factor Graphs, Matrix Determinant Lemma and Re-use of Calculation,” International Journal of Robotics Research (IJRR), no. 10, 2017.
    Kopitkov17ijrr.pdf DOI: 10.1177/0278364917721629
  11. D. Kopitkov, “Efficient Belief Space Planning in High-dimensional State Spaces by Exploiting Sparsity and Calculation Re-use,” Master's thesis, Technion - Israel Institute of Technology, 2017.
    Kopitkov17thesis.pdf Kopitkov17thesis.slides
  12. D. Kopitkov and V. Indelman, “Computationally Efficient Active Inference in High-Dimensional State Spaces,” in AI for Long-term Autonomy, workshop in conjunction with IEEE International Conference on Robotics and Automation (ICRA), May 2016.
    Kopitkov16icra_ws.pdf Kopitkov16icra_ws.poster
  13. D. Kopitkov and V. Indelman, “Computationally Efficient Decision Making Under Uncertainty in High-Dimensional State Spaces,” in IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Oct. 2016.
    Kopitkov16iros.pdf Kopitkov16iros.slides