Atanas Mirchev

21 papers A* 2Misc 2Journal 12Unranked 4
YearRankTypeTitle / Venue / Authors
2025 J jnl
Inherently Robust Control through Maximum-Entropy Learning-Based Rollout.
Trans. Mach. Learn. Res.
Felix Bok, Atanas Mirchev, Baris Kayalibay, Ole Jonas Wenzel, Patrick van der Smagt, Justin Bayer
2025 J jnl
Still Asking: How Good Are Query Optimizers, Really?
Proc. VLDB Endow.
Viktor Leis, Andrey Gubichev, Atanas Mirchev, Peter Boncz, Alfons Kemper, Thomas Neumann
2024 Misc conf
Exploring Under Constraints with Model-Based Actor-Critic and Safety Filters.
CoRL
Ahmed Agha, Baris Kayalibay, Atanas Mirchev, Patrick van der Smagt, Justin Bayer
2024 — —
Spatial State-Space Models (Räumliche Zustandsraummodelle)
Atanas Mirchev
2023 — conf
Filter-Aware Model-Predictive Control.
L4DC
Baris Kayalibay, Atanas Mirchev, Ahmed Agha, Patrick van der Smagt, Justin Bayer
2023 J jnl
Filter-Aware Model-Predictive Control.
CoRR
Baris Kayalibay, Atanas Mirchev, Ahmed Agha, Patrick van der Smagt, Justin Bayer
2022 Misc conf
PRISM: Probabilistic Real-Time Inference in Spatial World Models.
CoRL
Atanas Mirchev, Baris Kayalibay, Ahmed Agha, Patrick van der Smagt, Daniel Cremers, Justin Bayer
2022 J jnl
PRISM: Probabilistic Real-Time Inference in Spatial World Models.
CoRR
Atanas Mirchev, Baris Kayalibay, Ahmed Agha, Patrick van der Smagt, Daniel Cremers, Justin Bayer
2022 — conf
Tracking and Planning with Spatial World Models.
L4DC
Baris Kayalibay, Atanas Mirchev, Patrick van der Smagt, Justin Bayer
2022 J jnl
Tracking and Planning with Spatial World Models.
CoRR
Baris Kayalibay, Atanas Mirchev, Patrick van der Smagt, Justin Bayer
2021 A* conf
Mind the Gap when Conditioning Amortised Inference in Sequential Latent-Variable Models.
ICLR
Justin Bayer, Maximilian Soelch, Atanas Mirchev, Baris Kayalibay, Patrick van der Smagt
2021 J jnl
Mind the Gap when Conditioning Amortised Inference in Sequential Latent-Variable Models.
CoRR
Justin Bayer, Maximilian Soelch, Atanas Mirchev, Baris Kayalibay, Patrick van der Smagt
2021 A* conf
Variational State-Space Models for Localisation and Dense 3D Mapping in 6 DoF.
ICLR
Atanas Mirchev, Baris Kayalibay, Patrick van der Smagt, Justin Bayer
2020 — conf
3D Deep Learning for Biological Function Prediction from Physical Fields.
3DV
Vladimir Golkov, Marcin J. Skwark, Atanas Mirchev, Georgi Dikov, Alexander R. Geanes, Jeffrey L. Mendenhall, Jens Meiler, Daniel Cremers
2020 J jnl
Variational State-Space Models for Localisation and Dense 3D Mapping in 6 DoF.
CoRR
Atanas Mirchev, Baris Kayalibay, Patrick van der Smagt, Justin Bayer
2019 — conf
Approximate Bayesian Inference in Spatial Environments.
Robotics: Science and Systems
Atanas Mirchev, Baris Kayalibay, Maximilian Soelch, Patrick van der Smagt, Justin Bayer
2018 J jnl
Approximate Bayesian inference in spatial environments.
CoRR
Atanas Mirchev, Baris Kayalibay, Patrick van der Smagt, Justin Bayer
2018 J jnl
Classification of sparsely labeled spatio-temporal data through semi-supervised adversarial learning.
CoRR
Atanas Mirchev, Seyed-Ahmad Ahmadi
2018 J jnl
Query optimization through the looking glass, and what we found running the Join Order Benchmark.
VLDB J.
Viktor Leis, Bernhard Radke, Andrey Gubichev, Atanas Mirchev, Peter Boncz, Alfons Kemper, Thomas Neumann
2017 J jnl
3D Deep Learning for Biological Function Prediction from Physical Fields.
CoRR
Vladimir Golkov, Marcin J. Skwark, Atanas Mirchev, Georgi Dikov, Alexander R. Geanes, Jeffrey L. Mendenhall, Jens Meiler, Daniel Cremers
2015 J jnl
How Good Are Query Optimizers, Really?
Proc. VLDB Endow.
Viktor Leis, Andrey Gubichev, Atanas Mirchev, Peter Boncz, Alfons Kemper, Thomas Neumann