Maximilian Soelch

12 papers A* 2C 1Journal 6Unranked 3
YearRankTypeTitle / Venue / Authors
2026 J jnl
Latent Matters: Learning Deep State-Space Models.
CoRR
Alexej Klushyn, Richard Kurle, Maximilian Soelch, Botond Cseke, Patrick van der Smagt
2021 A* conf
Latent Matters: Learning Deep State-Space Models.
NeurIPS
Alexej Klushyn, Richard Kurle, Maximilian Soelch, Botond Cseke, Patrick van der Smagt
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
2019 — conf
Approximate Bayesian Inference in Spatial Environments.
Robotics: Science and Systems
Atanas Mirchev, Baris Kayalibay, Maximilian Soelch, Patrick van der Smagt, Justin Bayer
2019 — conf
On Deep Set Learning and the Choice of Aggregations.
ICANN (1)
Maximilian Soelch, Adnan Akhundov, Patrick van der Smagt, Justin Bayer
2019 J jnl
On Deep Set Learning and the Choice of Aggregations.
CoRR
Maximilian Soelch, Adnan Akhundov, Patrick van der Smagt, Justin Bayer
2019 C conf
Unsupervised Real-Time Control Through Variational Empowerment.
ISRR
Maximilian Karl, Philip Becker-Ehmck, Maximilian Soelch, Djalel Benbouzid, Patrick van der Smagt, Justin Bayer
2019 J jnl
Variational Tracking and Prediction with Generative Disentangled State-Space Models.
CoRR
Adnan Akhundov, Maximilian Soelch, Justin Bayer, Patrick van der Smagt
2017 — conf
Deep Variational Bayes Filters: Unsupervised Learning of State Space Models from Raw Data.
ICLR (Poster)
Maximilian Karl, Maximilian Soelch, Justin Bayer, Patrick van der Smagt
2016 J jnl
Deep Variational Bayes Filters: Unsupervised Learning of State Space Models from Raw Data.
CoRR
Maximilian Karl, Maximilian Soelch, Justin Bayer, Patrick van der Smagt
2016 J jnl
Variational Inference for On-line Anomaly Detection in High-Dimensional Time Series.
CoRR
Maximilian Soelch, Justin Bayer, Marvin Ludersdorfer, Patrick van der Smagt