Botond Cseke

Publication Activity (10 Years)

Years Active: 2008-2024
Publications (10 Years): 13

Top Topics

Distance Preserving

Top Venues

IEEE Trans. Robotics

Publications

Nutan Chen, Elie Aljalbout, Botond Cseke, Patrick van der Smagt
Guided Decoding for Robot Motion Generation and Adaption. CoRR (2024)
Felix Frank, Alexandros Paraschos, Patrick van der Smagt, Botond Cseke
Constrained Probabilistic Movement Primitives for Robot Trajectory Adaptation. IEEE Trans. Robotics 38 (4) (2022)
Nutan Chen, Patrick van der Smagt, Botond Cseke
Local distance preserving auto-encoders using Continuous k-Nearest Neighbours graphs. CoRR (2022)
Nutan Chen, Patrick van der Smagt, Botond Cseke
Local Distance Preserving Auto-encoders using Continuous kNN Graphs. TAG-ML (2022)
Alexej Klushyn, Richard Kurle, Maximilian Soelch, Botond Cseke, Patrick van der Smagt
Latent Matters: Learning Deep State-Space Models. NeurIPS (2021)
Felix Frank, Alexandros Paraschos, Patrick van der Smagt, Botond Cseke
Constrained Probabilistic Movement Primitives for Robot Trajectory Adaptation. CoRR (2021)
Richard Kurle, Botond Cseke, Alexej Klushyn, Patrick van der Smagt, Stephan Günnemann
Continual Learning with Bayesian Neural Networks for Non-Stationary Data. ICLR (2020)
Alexej Klushyn, Nutan Chen, Botond Cseke, Justin Bayer, Patrick van der Smagt
Increasing the Generalisaton Capacity of Conditional VAEs. ICANN (2) (2019)
Alexej Klushyn, Nutan Chen, Richard Kurle, Botond Cseke, Patrick van der Smagt
Learning Hierarchical Priors in VAEs. NeurIPS (2019)
Alexej Klushyn, Nutan Chen, Botond Cseke, Justin Bayer, Patrick van der Smagt
Increasing the Generalisaton Capacity of Conditional VAEs. CoRR (2019)
Alexej Klushyn, Nutan Chen, Richard Kurle, Botond Cseke, Patrick van der Smagt
Learning Hierarchical Priors in VAEs. CoRR (2019)
Sebastian Nowozin, Botond Cseke, Ryota Tomioka
f-GAN: Training Generative Neural Samplers using Variational Divergence Minimization. NIPS (2016)
Sebastian Nowozin, Botond Cseke, Ryota Tomioka
f-GAN: Training Generative Neural Samplers using Variational Divergence Minimization. CoRR (2016)
Botond Cseke, Tom Heskes
Properties of Bethe Free Energies and Message Passing in Gaussian Models. CoRR (2014)
Botond Cseke, Manfred Opper, Guido Sanguinetti
Approximate inference in latent Gaussian-Markov models from continuous time observations. NIPS (2013)
Botond Cseke, Tom Heskes
Bounds on the Bethe Free Energy for Gaussian Networks CoRR (2012)
Botond Cseke, Tom Heskes
Properties of Bethe Free Energies and Message Passing in Gaussian Models. J. Artif. Intell. Res. 41 (2011)
Botond Cseke, Tom Heskes
Approximate Marginals in Latent Gaussian Models. J. Mach. Learn. Res. 12 (2011)
Botond Cseke, Tom Heskes
Improving posterior marginal approximations in latent Gaussian models. AISTATS (2010)
Marcel A. J. van Gerven, Botond Cseke, Floris P. de Lange, Tom Heskes
Efficient Bayesian multivariate fMRI analysis using a sparsifying spatio-temporal prior. NeuroImage 50 (1) (2010)
Marcel van Gerven, Botond Cseke, Robert Oostenveld, Tom Heskes
Bayesian Source Localization with the Multivariate Laplace Prior. NIPS (2009)
Botond Cseke, Tom Heskes
Bounds on the Bethe Free Energy for Gaussian Networks. UAI (2008)