Botond Cseke

According to our database, Botond Cseke authored at least 17 papers between 2008 and 2024.

Collaborative distances:

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

2024

Guided Decoding for Robot Motion Generation and Adaption.

Nutan Chen, Elie Aljalbout, Botond Cseke, Patrick van der Smagt

CoRR, 2024

Guided Decoding for Robot On-line Motion Generation and Adaption.

Nutan Chen, Botond Cseke, Elie Aljalbout, Alexandros Paraschos, Marvin Alles, Patrick van der Smagt

Proceedings of the 23rd IEEE-RAS International Conference on Humanoid Robots, 2024

2022

Constrained Probabilistic Movement Primitives for Robot Trajectory Adaptation.

Felix Frank, Alexandros Paraschos, Patrick van der Smagt, Botond Cseke

IEEE Trans. Robotics, 2022

Local distance preserving auto-encoders using Continuous k-Nearest Neighbours graphs.

Nutan Chen, Patrick van der Smagt, Botond Cseke

CoRR, 2022

Local Distance Preserving Auto-encoders using Continuous kNN Graphs.

Nutan Chen, Patrick van der Smagt, Botond Cseke

Proceedings of the Topological, 2022

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

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

2016

f-GAN: Training Generative Neural Samplers using Variational Divergence Minimization.

Sebastian Nowozin, Botond Cseke, Ryota Tomioka

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

2013

Approximate inference in latent Gaussian-Markov models from continuous time observations.

Botond Cseke, Manfred Opper, Guido Sanguinetti

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

2011

Approximate Marginals in Latent Gaussian Models.

Botond Cseke, Tom Heskes

J. Mach. Learn. Res., 2011

Properties of Bethe Free Energies and Message Passing in Gaussian Models.

Botond Cseke, Tom Heskes

J. Artif. Intell. Res., 2011

2010

Efficient Bayesian multivariate fMRI analysis using a sparsifying spatio-temporal prior.

Marcel A. J. van Gerven, Botond Cseke, Floris P. de Lange, Tom Heskes

NeuroImage, 2010

Improving posterior marginal approximations in latent Gaussian models.

Botond Cseke, Tom Heskes

Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

2009

Bayesian Source Localization with the Multivariate Laplace Prior.

Marcel van Gerven, Botond Cseke, Robert Oostenveld, Tom Heskes

Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

2008

Bounds on the Bethe Free Energy for Gaussian Networks.

Botond Cseke, Tom Heskes

Proceedings of the UAI 2008, 2008