Botond Cseke
Botond Cseke
Volkswagen Data Lab
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f-gan: Training generative neural samplers using variational divergence minimization
S Nowozin, B Cseke, R Tomioka
Advances in Neural Information Processing Systems, 271-279, 2016
Network of epistatic interactions within a yeast snoRNA
O Puchta, B Cseke, H Czaja, D Tollervey, G Sanguinetti, G Kudla
Science 352 (6287), 840-844, 2016
Efficient Bayesian multivariate fMRI analysis using a sparsifying spatio-temporal prior
MAJ Van Gerven, B Cseke, FP De Lange, T Heskes
NeuroImage 50 (1), 150-161, 2010
Approximate marginals in latent Gaussian models
B Cseke, T Heskes
The Journal of Machine Learning Research 12, 417-454, 2011
Bayesian source localization with the multivariate Laplace prior
M Gerven, B Cseke, R Oostenveld, T Heskes
Advances in Neural Information Processing Systems 22, 2009
Learning hierarchical priors in vaes
A Klushyn, N Chen, R Kurle, B Cseke, P van der Smagt
Advances in neural information processing systems 32, 2019
MMDiff: quantitative testing for shape changes in ChIP-Seq data sets
G Schweikert, B Cseke, T Clouaire, A Bird, G Sanguinetti
BMC genomics 14 (1), 1-17, 2013
Continual Learning with Bayesian Neural Networks for Non-Stationary Data
R Kurle, B Cseke, A Klushyn, P van der Smagt, S Günnemann
International Conference on Learning Representations, 2020
Approximate inference in latent Gaussian-Markov models from continuous time observations
B Cseke, M Opper, G Sanguinetti
Advances in Neural Information Processing Systems 26, 2013
Expectation propagation for continuous time stochastic processes
B Cseke, D Schnoerr, M Opper, G Sanguinetti
Journal of Physics A: Mathematical and Theoretical 49 (49), 494002, 2016
Properties of Bethe free energies and message passing in Gaussian models
B Cseke, T Heskes
Journal of Artificial Intelligence Research 41, 1-24, 2011
Efficient low-order approximation of first-passage time distributions
D Schnoerr, B Cseke, R Grima, G Sanguinetti
Physical Review Letters 119 (21), 210601, 2017
Sparse approximate inference for spatio-temporal point process models
B Cseke, A Zammit-Mangion, T Heskes, G Sanguinetti
Journal of the American Statistical Association 111 (516), 1746-1763, 2016
Improving posterior marginal approximations in latent Gaussian models
B Cseke, T Heskes
Proceedings of the Thirteenth International Conference on Artificial …, 2010
Bounds on the Bethe free energy for Gaussian networks
B Cseke, T Heskes
arXiv preprint arXiv:1206.3243, 2012
Kernel principal component ranking: Robust ranking on noisy data
E Tsivtsivadze, B Cseke, TM Heskes
[Sl]: Pascal Lecture Series, 2009
Latent Matters: Learning Deep State-Space Models
A Klushyn, R Kurle, M Soelch, B Cseke, P van der Smagt
Advances in Neural Information Processing Systems 34, 10234-10245, 2021
Constrained Probabilistic Movement Primitives for Robot Trajectory Adaptation
F Frank, A Paraschos, P van der Smagt, B Cseke
IEEE Transactions on Robotics, 2021
Increasing the Generalisaton Capacity of Conditional VAEs
A Klushyn, N Chen, B Cseke, J Bayer, P Smagt
International Conference on Artificial Neural Networks, 779-791, 2019
Local distance preserving auto-encoders using Continuous k-Nearest Neighbours graphs
N Chen, P van der Smagt, B Cseke
arXiv preprint arXiv:2206.05909, 2022
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