Botond Cseke

Volkswagen Group (United States) — United States

Computer Science · Physical Sciences

13h-index2.2kcitations36works1.62yr avg
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Research Topics

Gaussian Processes and Bayesian Inference(10), Bayesian Methods and Mixture Models(7), Statistical Methods and Bayesian Inference(6), Generative Adversarial Networks and Image Synthesis(6), Statistical Methods and Inference(4)

Publications36 total

Latent Matters: Learning Deep State-Space Models
arXiv (Cornell University)·2026· 8 citedOpen Access
FlowQ: Energy-Guided Flow Policies for Offline Reinforcement Learning
arXiv (Cornell University)·2025Open Access
Fast Preserving Local Distances and Topology in Auto-encoders
Lecture notes in computer science·2025
Guided Decoding for Robot On-line Motion Generation and Adaption
2024
Guided Decoding for Robot On-line Motion Generation and Adaption
arXiv (Cornell University)·2024Open Access
Local Distance Preserving Auto-encoders using Continuous k-Nearest Neighbours Graphs
arXiv (Cornell University)·2022· 1 citedOpen Access
Constrained Probabilistic Movement Primitives for Robot Trajectory Adaptation
IEEE Transactions on Robotics·2021· 55 citedOpen Access
Continual Learning with Bayesian Neural Networks for Non-Stationary Data
International Conference on Learning Representations·2020· 36 cited
Increasing the Generalisation Capacity of Conditional VAEs
arXiv (Cornell University)·2019Open Access
Learning Hierarchical Priors in VAEs
arXiv (Cornell University)·2019· 6 citedOpen Access
Increasing the Generalisaton Capacity of Conditional VAEs
Lecture notes in computer science·2019
Efficient Low-Order Approximation of First-Passage Time Distributions
Physical Review Letters·2017· 19 citedOpen Access
Approximating first-passage time distributions via sequential Bayesian computation
arXiv (Cornell University)·2017Open Access
f-GAN: Training Generative Neural Samplers using Variational Divergence Minimization
arXiv (Cornell University)·2016· 635 citedOpen Access
f-GAN: Training Generative Neural Samplers using Variational Divergence\n Minimization
arXiv (Cornell University)·2016· 607 citedOpen Access
Network of epistatic interactions within a yeast snoRNA
Science·2016· 136 citedOpen Access
Sparse Approximate Inference for Spatio-Temporal Point Process Models
Journal of the American Statistical Association·2015· 16 citedOpen Access
Expectation propagation for diffusion processes by moment closure approximations
arXiv (Cornell University)·2015· 2 citedOpen Access
Sparse Approximate Inference for Spatio-Temporal Point Process Models
Figshare·2015Open Access
Approximate inference in latent Gaussian-Markov models from continuous time observations
Edinburgh Research Explorer (University of Edinburgh)·2013· 9 citedOpen Access
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Frequent Co-authors

Guido Sanguinetti(14), Tom Heskes(12), Patrick van der Smagt(11), Nutan Chen(8), Manfred Opper(5), Alexej Klushyn(5), David Schnoerr(4), Richard Kurle(3), Sebastian Nowozin(2), Ryota Tomioka(2), Marcel van Gerven(2), Alexandros Paraschos(2), Ramon Grima(2), Andrew Zammit‐Mangion(2), Elie Aljalbout(2), Marvin Alles(2), Justin Bayer(2), Andrew Zammit Mangion(2), Olga Puchta(1), Hubert Czaja(1)