Maximilian Soelch

Publication Activity (10 Years)

Years Active: 2016-2021
Publications (10 Years): 11

Top Topics

Variational Bayes

Top Venues

Publications

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