Maximilian Soelch

According to our database, Maximilian Soelch authored at least 12 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2024

Transforming Computer-Based Exams with BYOD: An Empirical Study.

Maximilian Sölch, Markus Paulsen, Stephan Krusche

Proceedings of the 24th Koli Calling International Conference on Computing Education Research, 2024

2023

Integrating Competency-Based Education in Interactive Learning Systems.

Maximilian Sölch, Moritz Aberle, Stephan Krusche

CoRR, 2023

Is Online Teaching Dead After COVID-19? Student Preferences for Programming Courses.

Stefanie Manger, Maximilian Sölch, Matthias Linhuber, Christoph Weinhuber, Philipp Zagar, Stephan Krusche

Proceedings of the 35th International Conference on Software Engineering Education and Training, 2023

2021

Uncovering dynamics: Learning and amortized inference for state-space models.

Maximilian Sölch

PhD thesis, 2021

Latent Matters: Learning Deep State-Space Models.

Alexej Klushyn, Richard Kurle, Maximilian Soelch, Botond Cseke, Patrick van der Smagt

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

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

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

Proceedings of the 9th International Conference on Learning Representations, 2021

2019

Variational Tracking and Prediction with Generative Disentangled State-Space Models.

Adnan Akhundov, Maximilian Soelch, Justin Bayer, Patrick van der Smagt

CoRR, 2019

Approximate Bayesian Inference in Spatial Environments.

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

Proceedings of the Robotics: Science and Systems XV, 2019

Unsupervised Real-Time Control Through Variational Empowerment.

Maximilian Karl, Philip Becker-Ehmck, Maximilian Soelch, Djalel Benbouzid, Patrick van der Smagt, Justin Bayer

Proceedings of the Robotics Research, 2019

On Deep Set Learning and the Choice of Aggregations.

Maximilian Soelch, Adnan Akhundov, Patrick van der Smagt, Justin Bayer

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2019: Theoretical Neural Computation, 2019

2017

Deep Variational Bayes Filters: Unsupervised Learning of State Space Models from Raw Data.

Maximilian Karl, Maximilian Soelch, Justin Bayer, Patrick van der Smagt

Proceedings of the 5th International Conference on Learning Representations, 2017

2016

Variational Inference for On-line Anomaly Detection in High-Dimensional Time Series.

Maximilian Soelch, Justin Bayer, Marvin Ludersdorfer, Patrick van der Smagt

CoRR, 2016