| A CMOS-based sensor array for in-vitro neural tissue interfacing with 4225 recording sites and 1024 stimulation sites G Bertotti, D Velychko, N Dodel, S Keil, D Wolansky, B Tillak, M Schreiter, ... 2014 IEEE Biomedical Circuits and Systems Conference (BioCAS) Proceedings …, 2014 | 77 | 2014 |
| Coupling Gaussian process dynamical models with product-of-experts kernels D Velychko, D Endres, N Taubert, MA Giese Artificial Neural Networks and Machine Learning–ICANN 2014: 24th …, 2014 | 10 | 2014 |
| Making the coupled Gaussian process dynamical model modular and scalable with variational approximations D Velychko, B Knopp, D Endres Entropy 20 (10), 724, 2018 | 8 | 2018 |
| Predicting perceived naturalness of human animations based on generative movement primitive models B Knopp, D Velychko, J Dreibrodt, D Endres ACM Transactions on Applied Perception (TAP) 16 (3), 1-18, 2019 | 7 | 2019 |
| Simultaneous stimulation and recording of retinal action potentials using capacitively coupled high-density CMOS-based MEAs D Velychko, M Eickenscheidt, R Thewes, G Zeck Proc. 9th Int. Meeting on Substrate-Integrated Microelectrodes, Germany, 2014 | 7 | 2014 |
| The ELBO of variational autoencoders converges to a sum of entropies S Damm, D Forster, D Velychko, Z Dai, A Fischer, J Lücke International Conference on Artificial Intelligence and Statistics, 3931-3960, 2023 | 3 | 2023 |
| The ELBO of Variational Autoencoders Converges to a Sum of Three Entropies S Damm, D Forster, D Velychko, Z Dai, A Fischer, J Lücke arXiv preprint arXiv:2010.14860, 2020 | 3 | 2020 |
| Evaluating perceptual predictions based on movement primitive models in VR-and online-experiments B Knopp, D Velychko, J Dreibrodt, AC Schütz, D Endres ACM Symposium on Applied Perception 2020, 1-9, 2020 | 3 | 2020 |
| WINDOW CORRECTION AT TIME SERIES REALIZATION OF THE NARROW-BAND GAUSSIAN STOCHASTIC PROCESS. A Velychko, D Velychko, A Vichkan, K Netrebenko Eastern-European Journal of Enterprise Technologies 4 (9), 2014 | 3 | 2014 |
| The variational coupled gaussian process dynamical model D Velychko, B Knopp, D Endres Artificial Neural Networks and Machine Learning–ICANN 2017: 26th …, 2017 | 2 | 2017 |
| Learning Sparse Codes with Entropy-Based ELBOs D Velychko, S Damm, A Fischer, J Lücke International Conference on Artificial Intelligence and Statistics, 2089-2097, 2024 | | 2024 |
| Probabilistic Models of Motor Production D Velychko Philipps-Universität Marburg, 2020 | | 2020 |
| Supplementary Material: The Variational Coupled Gaussian Process Dynamical Model D Velychko, B Knopp, D Endres | | 2017 |
