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2020 – today
- 2024
[c11]Nutan Chen, Botond Cseke, Elie Aljalbout, Alexandros Paraschos, Marvin Alles, Patrick van der Smagt:
Guided Decoding for Robot On-line Motion Generation and Adaption. Humanoids 2024: 321-327- [i8]Nutan Chen, Elie Aljalbout, Botond Cseke, Patrick van der Smagt
:
Guided Decoding for Robot Motion Generation and Adaption. CoRR abs/2403.15239 (2024) - 2022
- [j4]Felix Frank, Alexandros Paraschos, Patrick van der Smagt, Botond Cseke:
Constrained Probabilistic Movement Primitives for Robot Trajectory Adaptation. IEEE Trans. Robotics 38(4): 2276-2294 (2022) - [c10]Nutan Chen, Patrick van der Smagt, Botond Cseke:
Local Distance Preserving Auto-encoders using Continuous kNN Graphs. TAG-ML 2022: 55-66 - [i7]Nutan Chen, Patrick van der Smagt, Botond Cseke:
Local distance preserving auto-encoders using Continuous k-Nearest Neighbours graphs. CoRR abs/2206.05909 (2022) - 2021
- [c9]Alexej Klushyn, Richard Kurle, Maximilian Soelch, Botond Cseke, Patrick van der Smagt:
Latent Matters: Learning Deep State-Space Models. NeurIPS 2021: 10234-10245 - [i6]Felix Frank, Alexandros Paraschos, Patrick van der Smagt, Botond Cseke:
Constrained Probabilistic Movement Primitives for Robot Trajectory Adaptation. CoRR abs/2101.12561 (2021) - 2020
- [c8]Richard Kurle, Botond Cseke, Alexej Klushyn, Patrick van der Smagt, Stephan Günnemann:
Continual Learning with Bayesian Neural Networks for Non-Stationary Data. ICLR 2020
2010 – 2019
- 2019
- [c7]Alexej Klushyn, Nutan Chen, Botond Cseke, Justin Bayer, Patrick van der Smagt:
Increasing the Generalisaton Capacity of Conditional VAEs. ICANN (2) 2019: 779-791 - [c6]Alexej Klushyn, Nutan Chen, Richard Kurle, Botond Cseke, Patrick van der Smagt:
Learning Hierarchical Priors in VAEs. NeurIPS 2019: 2866-2875 - [i5]Alexej Klushyn, Nutan Chen, Richard Kurle, Botond Cseke, Patrick van der Smagt:
Learning Hierarchical Priors in VAEs. CoRR abs/1905.04982 (2019) - [i4]Alexej Klushyn, Nutan Chen, Botond Cseke, Justin Bayer, Patrick van der Smagt:
Increasing the Generalisaton Capacity of Conditional VAEs. CoRR abs/1908.08750 (2019) - 2016
- [c5]Sebastian Nowozin, Botond Cseke, Ryota Tomioka:
f-GAN: Training Generative Neural Samplers using Variational Divergence Minimization. NIPS 2016: 271-279 - [i3]Sebastian Nowozin, Botond Cseke, Ryota Tomioka:
f-GAN: Training Generative Neural Samplers using Variational Divergence Minimization. CoRR abs/1606.00709 (2016) - 2014
- [i2]Botond Cseke, Tom Heskes:
Properties of Bethe Free Energies and Message Passing in Gaussian Models. CoRR abs/1401.3877 (2014) - 2013
- [c4]Botond Cseke, Manfred Opper, Guido Sanguinetti:
Approximate inference in latent Gaussian-Markov models from continuous time observations. NIPS 2013: 971-979 - 2012
- [i1]Botond Cseke, Tom Heskes:
Bounds on the Bethe Free Energy for Gaussian Networks. CoRR abs/1206.3243 (2012) - 2011
- [j3]Botond Cseke, Tom Heskes:
Properties of Bethe Free Energies and Message Passing in Gaussian Models. J. Artif. Intell. Res. 41: 1-24 (2011) - [j2]Botond Cseke, Tom Heskes:
Approximate Marginals in Latent Gaussian Models. J. Mach. Learn. Res. 12: 417-454 (2011) - 2010
- [j1]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): 150-161 (2010) - [c3]Botond Cseke, Tom Heskes:
Improving posterior marginal approximations in latent Gaussian models. AISTATS 2010: 121-128
2000 – 2009
- 2009
- [c2]Marcel van Gerven, Botond Cseke, Robert Oostenveld, Tom Heskes:
Bayesian Source Localization with the Multivariate Laplace Prior. NIPS 2009: 1901-1909 - 2008
- [c1]Botond Cseke, Tom Heskes:
Bounds on the Bethe Free Energy for Gaussian Networks. UAI 2008: 97-104
Coauthor Index
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