| Ising models for binary clustering via adiabatic quantum computing C Bauckhage, E Brito, K Cvejoski, C Ojeda, R Sifa, S Wrobel Energy Minimization Methods in Computer Vision and Pattern Recognition: 11th …, 2018 | 29 | 2018 |
| Adiabatic quantum computing for binary clustering C Bauckhage, E Brito, K Cvejoski, C Ojeda, R Sifa, S Wrobel arXiv preprint arXiv:1706.05528, 2017 | 8 | 2017 |
| Informed pre-training on prior knowledge L von Rueden, S Houben, K Cvejoski, C Bauckhage, N Piatkowski arXiv preprint arXiv:2205.11433, 2022 | 6 | 2022 |
| Knowledge Augmented Machine Learning with Applications in Autonomous Driving: A Survey J Wörmann, D Bogdoll, E Bührle, H Chen, EF Chuo, K Cvejoski, L van Elst, ... arXiv preprint arXiv:2205.04712, 2022 | 4 | 2022 |
| Dynamic Review-based Recommenders K Cvejoski, RJ Sánchez, C Bauckhage, C Ojeda Data Science–Analytics and Applications: Proceedings of the 4th …, 2022 | 4 | 2022 |
| Introduction to machine learning with robots and playful learning V Olari, K Cvejoski, Ø Eide Proceedings of the AAAI Conference on Artificial Intelligence 35 (17), 15630 …, 2021 | 4 | 2021 |
| Towards German word embeddings: A use case with predictive sentiment analysis E Brito, R Sifa, K Cvejoski, C Ojeda, C Bauckhage Data Science–Analytics and Applications: Proceedings of the 1st …, 2017 | 4 | 2017 |
| Towards shortest paths via adiabatic quantum computing C Bauckhage, E Brito, K Cvejoski, C Ojeda, J Schücker, R Sifa Proc. Mining Learn. Graphs, 2018 | 3 | 2018 |
| Interpretable matrix factorization with stochasticity constrained nonnegative DEDICOM R Sifa, C Ojeda, K Cvejoski, C Bauckhage Proc. KDML, 2017 | 3 | 2017 |
| Inverse dynamical inheritance in stack exchange taxonomies C Ojeda, K Cvejoski, R Sifa, C Bauckhage Proceedings of the International AAAI Conference on Web and Social Media 11 …, 2017 | 3 | 2017 |
| Learning deep generative models for queuing systems C Ojeda, K Cvejoski, B Georgiev, C Bauckhage, J Schuecker, ... Proceedings of the AAAI Conference on Artificial Intelligence 35 (10), 9214-9222, 2021 | 2 | 2021 |
| 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 | 2 | 2021 |
| Recurrent point review models K Cvejoski, RJ Sánchez, B Georgiev, C Bauckhage, C Ojeda 2020 International Joint Conference on Neural Networks (IJCNN), 1-8, 2020 | 2 | 2020 |
| Recurrent point processes for dynamic review models K Cvejoski, RJ Sanchez, B Georgiev, J Schuecker, C Bauckhage, ... arXiv preprint arXiv:1912.04132, 2019 | 2 | 2019 |
| Variable Attention and Variable Noise: Forecasting User Activity. C Ojeda, K Cvejoski, R Sifa, C Bauckhage LWDA, 347-358, 2016 | 2 | 2016 |
| Combining Variational Autoencoders and Transformer Language Models for Improved Password Generation D Biesner, K Cvejoski, R Sifa Proceedings of the 17th International Conference on Availability …, 2022 | 1 | 2022 |
| 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 | 1 | 2021 |
| Patterns and outliers in temporal point processes CAM Ojeda, K Cvejoski, R Sifa, J Schuecker, C Bauckhage Intelligent Systems and Applications: Proceedings of the 2019 Intelligent …, 2020 | 1 | 2020 |
| Recurrent adversarial service times C Ojeda, K Cvejosky, RJ Sánchez, J Schuecker, B Georgiev, ... arXiv preprint arXiv:1906.09808, 2019 | 1 | 2019 |
| Adiabatic Quantum argmax Computation C Bauckhage, K Cvejoski, C Ojeda, J Schücker, R Sifa researchgate, Tech. Rep, 2018 | 1 | 2018 |
