| How good are query optimizers, really? V Leis, A Gubichev, A Mirchev, P Boncz, A Kemper, T Neumann Proceedings of the VLDB Endowment 9 (3), 204-215, 2015 | 762 | 2015 |
| Query optimization through the looking glass, and what we found running the join order benchmark V Leis, B Radke, A Gubichev, A Mirchev, P Boncz, A Kemper, T Neumann The VLDB Journal 27, 643-668, 2018 | 186 | 2018 |
| Survey of concepts for QoS improvements via SDN A Mirchev Future internet (FI) and innovative internet technologies and mobile …, 2015 | 33 | 2015 |
| Approximate bayesian inference in spatial environments A Mirchev, B Kayalibay, M Soelch, P van der Smagt, J Bayer arXiv preprint arXiv:1805.07206, 2018 | 24 | 2018 |
| 3D deep learning for biological function prediction from physical fields V Golkov, MJ Skwark, A Mirchev, G Dikov, AR Geanes, J Mendenhall, ... 2020 International Conference on 3D Vision (3DV), 928-937, 2020 | 20 | 2020 |
| Mind the gap when conditioning amortised inference in sequential latent-variable models J Bayer, M Soelch, A Mirchev, B Kayalibay, P van der Smagt arXiv preprint arXiv:2101.07046, 2021 | 18 | 2021 |
| Variational state-space models for localisation and dense 3d mapping in 6 dof A Mirchev, B Kayalibay, P van der Smagt, J Bayer arXiv preprint arXiv:2006.10178, 2020 | 11 | 2020 |
| Classification of sparsely labeled spatio-temporal data through semi-supervised adversarial learning A Mirchev, SA Ahmadi arXiv preprint arXiv:1801.08712, 2018 | 5 | 2018 |
| Tracking and planning with spatial world models B Kayalibay, A Mirchev, P van der Smagt, J Bayer Learning for Dynamics and Control Conference, 124-137, 2022 | 3* | 2022 |
| Navigation and planning in latent maps B Kayalibay, A Mirchev, M Soelch, P Van Der Smagt, J Bayer FAIM workshop “Prediction and Generative Modeling in Reinforcement Learning 4, 2018 | 3 | 2018 |
| PRISM: Probabilistic Real-Time Inference in Spatial World Models A Mirchev, B Kayalibay, A Agha, P van der Smagt, D Cremers, J Bayer Conference on Robot Learning, 161-174, 2023 | 2 | 2023 |
| Less Suboptimal Learning and Control in Variational POMDPs B Kayalibay, A Mirchev, P van der Smagt, J Bayer | 2 | |
| Spatial State-Space Models: Dense Probabilistic Prediction and Inference in 3D AG Mirchev Technische Universität München, 2024 | | 2024 |
| Filter-Aware Model-Predictive Control B Kayalibay, A Mirchev, A Agha, P van der Smagt, J Bayer Learning for Dynamics and Control Conference, 1441-1454, 2023 | | 2023 |
