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Tracking and Planning with Spatial World Models


Jan 25, 2022
Baris Kayalibay, Atanas Mirchev, Patrick van der Smagt, Justin Bayer


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Mind the Gap when Conditioning Amortised Inference in Sequential Latent-Variable Models


Jan 18, 2021
Justin Bayer, Maximilian Soelch, Atanas Mirchev, Baris Kayalibay, Patrick van der Smagt

* Published as a conference paper at ICLR 2021 (Poster) 

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Variational State-Space Models for Localisation and Dense 3D Mapping in 6 DoF


Jun 17, 2020
Atanas Mirchev, Baris Kayalibay, Patrick van der Smagt, Justin Bayer


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Learning Flat Latent Manifolds with VAEs


Feb 12, 2020
Nutan Chen, Alexej Klushyn, Francesco Ferroni, Justin Bayer, Patrick van der Smagt

* 13 pages 

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Variational Tracking and Prediction with Generative Disentangled State-Space Models


Oct 14, 2019
Adnan Akhundov, Maximilian Soelch, Justin Bayer, Patrick van der Smagt


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Increasing the Generalisation Capacity of Conditional VAEs


Sep 10, 2019
Alexej Klushyn, Nutan Chen, Botond Cseke, Justin Bayer, Patrick van der Smagt


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Increasing the Generalisaton Capacity of Conditional VAEs


Aug 23, 2019
Alexej Klushyn, Nutan Chen, Botond Cseke, Justin Bayer, Patrick van der Smagt


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On Deep Set Learning and the Choice of Aggregations


Mar 18, 2019
Maximilian Soelch, Adnan Akhundov, Patrick van der Smagt, Justin Bayer


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Bayesian Learning of Neural Network Architectures


Jan 27, 2019
Georgi Dikov, Patrick van der Smagt, Justin Bayer

* The 22nd International Conference on Artificial Intelligence and Statistics (AISTATS 2019) 

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