Alexej Klushyn

According to our database, Alexej Klushyn authored at least 9 papers between 2018 and 2021.

Collaborative distances:

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

2021

Latent Matters: Amortised Variational Inference With Constrained Optimisation and Learnable Priors.

Alexej Klushyn

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

2020

Learning Flat Latent Manifolds with VAEs.

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

Proceedings of the 37th International Conference on Machine Learning, 2020

Continual Learning with Bayesian Neural Networks for Non-Stationary Data.

Richard Kurle, Botond Cseke, Alexej Klushyn, Patrick van der Smagt, Stephan Günnemann

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

Learning Hierarchical Priors in VAEs.

Alexej Klushyn, Nutan Chen, Richard Kurle, Botond Cseke, Patrick van der Smagt

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Increasing the Generalisaton Capacity of Conditional VAEs.

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

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

Fast Approximate Geodesics for Deep Generative Models.

Nutan Chen, Francesco Ferroni, Alexej Klushyn, Alexandros Paraschos, Justin Bayer, Patrick van der Smagt

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

2018

Active Learning based on Data Uncertainty and Model Sensitivity.

Nutan Chen, Alexej Klushyn, Alexandros Paraschos, Djalel Benbouzid, Patrick van der Smagt

Proceedings of the 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2018

Metrics for Deep Generative Models.

Nutan Chen, Alexej Klushyn, Richard Kurle, Xueyan Jiang, Justin Bayer, Patrick van der Smagt

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018