| Informed machine learning–a taxonomy and survey of integrating prior knowledge into learning systems L Von Rueden, S Mayer, K Beckh, B Georgiev, S Giesselbach, R Heese, ... IEEE Transactions on Knowledge and Data Engineering 35 (1), 614-633, 2021 | 609 | 2021 |
| Nodal geometry, heat diffusion and Brownian motion B Georgiev, M Mukherjee Analysis & Pde 11 (1), 133-148, 2017 | 26 | 2017 |
| On the lower bound of the inner radius of nodal domains B Georgiev The Journal of Geometric Analysis 29 (2), 1546-1554, 2019 | 15 | 2019 |
| On maximizing the fundamental frequency of the complement of an obstacle B Georgiev, M Mukherjee Comptes Rendus. Mathématique 356 (4), 406-411, 2018 | 13 | 2018 |
| Neural abstract reasoner V Kolev, B Georgiev, S Penkov arXiv preprint arXiv:2011.09860, 2020 | 12 | 2020 |
| Gradient-free quantum optimization on NISQ devices L Franken, B Georgiev, S Muecke, M Wolter, N Piatkowski, C Bauckhage arXiv preprint arXiv:2012.13453, 2020 | 12 | 2020 |
| Explorations in Quantum Neural Networks with Intermediate Measurements. L Franken, B Georgiev ESANN, 297-302, 2020 | 12 | 2020 |
| Some remarks on nodal geometry in the smooth setting B Georgiev, M Mukherjee Calculus of Variations and Partial Differential Equations 58, 1-25, 2019 | 12 | 2019 |
| Polynomial upper bound on interior Steklov nodal sets B Georgiev, G Roy-Fortin Journal of Spectral Theory 9 (3), 897-919, 2019 | 11 | 2019 |
| Informed machine learning-a taxonomy and survey of integrating knowledge into learning systems (2020) L Von Rueden, S Mayer, K Beckh, B Georgiev, S Giesselbach, R Heese, ... arXiv preprint arXiv:1903.12394, 1903 | 10 | 1903 |
| A prior-based approximate latent riemannian metric G Arvanitidis, B Georgiev, B Schölkopf arXiv preprint arXiv:2103.05290, 2021 | 9 | 2021 |
| RatVec: A General Approach for Low-dimensional Distributed Vector Representations via Rational Kernels. E Brito, B Georgiev, D Domingo-Fernández, CT Hoyt, C Bauckhage LWDA, 74-78, 2019 | 7 | 2019 |
| Quantum circuit evolution on nisq devices L Franken, B Georgiev, S Mucke, M Wolter, R Heese, C Bauckhage, ... 2022 IEEE Congress on Evolutionary Computation (CEC), 1-8, 2022 | 5 | 2022 |
| Generative deep learning techniques for password generation D Biesner, K Cvejoski, B Georgiev, R Sifa, E Krupicka arXiv preprint arXiv:2012.05685, 2020 | 5 | 2020 |
| On a Sweeping Process with the Cone of Limiting Normals B Georgiev, N Ribarska Comptes rendus de l’Académie bulgare des Sciences 66 (5), 2013 | 5 | 2013 |
| Some applications of heat flow to Laplace eigenfunctions B Georgiev, M Mukherjee Communications in Partial Differential Equations 47 (4), 677-700, 2022 | 4 | 2022 |
| Advances in password recovery using generative deep learning techniques D Biesner, K Cvejoski, B Georgiev, R Sifa, E Krupicka Artificial Neural Networks and Machine Learning–ICANN 2021: 30th …, 2021 | 3 | 2021 |
| A spectral gap estimate and applications B Georgiev, M Mukherjee, S Steinerberger arXiv preprint arXiv:1612.08565, 2016 | 3 | 2016 |
| On Dirichlet eigenvalues of regular polygons D Berghaus, B Georgiev, H Monien, D Radchenko arXiv preprint arXiv:2103.01057, 2021 | 2 | 2021 |
| Switching dynamical systems with deep neural networks C Ojeda, B Georgiev, K Cvejoski, J Schucker, C Bauckhage, RJ Sánchez 2020 25th International Conference on Pattern Recognition (ICPR), 6305-6312, 2021 | 2 | 2021 |
