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Atanas Mirchev
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2020 – today
- 2024
- [b1]Atanas Mirchev:
Spatial State-Space Models (Räumliche Zustandsraummodelle). TU Munich, Germany, 2024 - 2023
- [c7]Baris Kayalibay, Atanas Mirchev, Ahmed Agha, Patrick van der Smagt, Justin Bayer:
Filter-Aware Model-Predictive Control. L4DC 2023: 1441-1454 - [i8]Baris Kayalibay, Atanas Mirchev, Ahmed Agha, Patrick van der Smagt
, Justin Bayer:
Filter-Aware Model-Predictive Control. CoRR abs/2304.10246 (2023) - 2022
- [c6]Atanas Mirchev, Baris Kayalibay, Ahmed Agha, Patrick van der Smagt, Daniel Cremers, Justin Bayer:
PRISM: Probabilistic Real-Time Inference in Spatial World Models. CoRL 2022: 161-174 - [c5]Baris Kayalibay, Atanas Mirchev, Patrick van der Smagt, Justin Bayer:
Tracking and Planning with Spatial World Models. L4DC 2022: 124-137 - [i7]Baris Kayalibay, Atanas Mirchev, Patrick van der Smagt, Justin Bayer:
Tracking and Planning with Spatial World Models. CoRR abs/2201.10335 (2022) - [i6]Atanas Mirchev, Baris Kayalibay, Ahmed Agha, Patrick van der Smagt
PRISM: Probabilistic Real-Time Inference in Spatial World Models. CoRR abs/2212.02988 (2022) - 2021
- [c4]Justin Bayer, Maximilian Soelch, Atanas Mirchev, Baris Kayalibay, Patrick van der Smagt
Mind the Gap when Conditioning Amortised Inference in Sequential Latent-Variable Models. ICLR 2021 - [c3]Atanas Mirchev, Baris Kayalibay, Patrick van der Smagt
Variational State-Space Models for Localisation and Dense 3D Mapping in 6 DoF. ICLR 2021 - [i5]Justin Bayer, Maximilian Soelch, Atanas Mirchev, Baris Kayalibay, Patrick van der Smagt:
Mind the Gap when Conditioning Amortised Inference in Sequential Latent-Variable Models. CoRR abs/2101.07046 (2021) - 2020
- [c2]Vladimir Golkov, Marcin J. Skwark
3D Deep Learning for Biological Function Prediction from Physical Fields. 3DV 2020: 928-937 - [i4]Atanas Mirchev, Baris Kayalibay, Patrick van der Smagt
Variational State-Space Models for Localisation and Dense 3D Mapping in 6 DoF. CoRR abs/2006.10178 (2020)
2010 – 2019
- 2019
- [c1]Atanas Mirchev, Baris Kayalibay, Maximilian Soelch, Patrick van der Smagt
Approximate Bayesian Inference in Spatial Environments. Robotics: Science and Systems 2019 - 2018
- [j2]Viktor Leis, Bernhard Radke, Andrey Gubichev, Atanas Mirchev, Peter A. Boncz, Alfons Kemper, Thomas Neumann:
Query optimization through the looking glass, and what we found running the Join Order Benchmark. VLDB J. 27(5): 643-668 (2018) - [i3]Atanas Mirchev, Seyed-Ahmad Ahmadi:
Classification of sparsely labeled spatio-temporal data through semi-supervised adversarial learning. CoRR abs/1801.08712 (2018) - [i2]Atanas Mirchev, Baris Kayalibay, Patrick van der Smagt, Justin Bayer:
Approximate Bayesian inference in spatial environments. CoRR abs/1805.07206 (2018) - 2017
- [i1]Vladimir Golkov, Marcin J. Skwark, Atanas Mirchev, Georgi Dikov, Alexander R. Geanes, Jeffrey L. Mendenhall, Jens Meiler, Daniel Cremers:
3D Deep Learning for Biological Function Prediction from Physical Fields. CoRR abs/1704.04039 (2017) - 2015
- [j1]Viktor Leis, Andrey Gubichev, Atanas Mirchev, Peter A. Boncz, Alfons Kemper, Thomas Neumann:
How Good Are Query Optimizers, Really? Proc. VLDB Endow. 9(3): 204-215 (2015)
Coauthor Index
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