Maximilian Soelch

Affiliations:
  • argmax.ai, Munich, Germany
  • Volkswagen Group Machine Learning Research Lab, Munich, Germany
  • TU Munich, Department of Informatics, Germany (former)


According to our database1, Maximilian Soelch authored at least 11 papers between 2016 and 2023.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2023
Integrating Competency-Based Education in Interactive Learning Systems.
CoRR, 2023

Is Online Teaching Dead After COVID-19? Student Preferences for Programming Courses.
Proceedings of the 35th International Conference on Software Engineering Education and Training, 2023

2021
Uncovering dynamics: Learning and amortized inference for state-space models.
PhD thesis, 2021

Latent Matters: Learning Deep State-Space Models.
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.
Proceedings of the 9th International Conference on Learning Representations, 2021

2019
Variational Tracking and Prediction with Generative Disentangled State-Space Models.
CoRR, 2019

Approximate Bayesian Inference in Spatial Environments.
Proceedings of the Robotics: Science and Systems XV, 2019

Unsupervised Real-Time Control Through Variational Empowerment.
Proceedings of the Robotics Research, 2019

On Deep Set Learning and the Choice of Aggregations.
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.
Proceedings of the 5th International Conference on Learning Representations, 2017

2016
Variational Inference for On-line Anomaly Detection in High-Dimensional Time Series.
CoRR, 2016


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