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Kostadin Cvejoski
Kostadin Cvejoski
Fraunhofer IAIS, LAMARR Institute
Verified email at iais.fraunhofer.de
Title
Cited by
Cited by
Year
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
352018
Introduction to machine learning with robots and playful learning
V Olari, K Cvejoski, Ĝ Eide
Proceedings of the AAAI Conference on Artificial Intelligence 35 (17), 15630 …, 2021
182021
Knowledge augmented machine learning with applications in autonomous driving: A survey
J Wörmann, D Bogdoll, C Brunner, E Bührle, H Chen, EF Chuo, ...
arXiv preprint arXiv:2205.04712, 2022
122022
Adiabatic quantum computing for binary clustering
C Bauckhage, E Brito, K Cvejoski, C Ojeda, R Sifa, S Wrobel
arXiv preprint arXiv:1706.05528, 2017
112017
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
102022
Informed pre-training on prior knowledge
L von Rueden, S Houben, K Cvejoski, C Bauckhage, N Piatkowski
arXiv preprint arXiv:2205.11433, 2022
102022
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
82021
Towards shortest paths via adiabatic quantum computing
C Bauckhage, E Brito, K Cvejoski, C Ojeda, J Schücker, R Sifa
Proc. Mining Learn. Graphs, 2018
72018
Dynamic Review-based Recommenders
K Cvejoski, RJ Sánchez, C Bauckhage, C Ojeda
Data Science–Analytics and Applications: Proceedings of the 4th …, 2022
52022
Generative deep learning techniques for password generation
D Biesner, K Cvejoski, B Georgiev, R Sifa, E Krupicka
arXiv preprint arXiv:2012.05685, 2020
52020
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
52017
Neural dynamic focused topic model
K Cvejoski, RJ Sánchez, C Ojeda
Proceedings of the AAAI Conference on Artificial Intelligence 37 (11), 12719 …, 2023
42023
Recurrent point processes for dynamic review models
K Cvejoski, RJ Sanchez, B Georgiev, J Schuecker, C Bauckhage, ...
arXiv preprint arXiv:1912.04132, 2019
42019
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
42017
The future is different: Large pre-trained language models fail in prediction tasks
K Cvejoski, RJ Sánchez, C Ojeda
arXiv preprint arXiv:2211.00384, 2022
32022
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
32021
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
32020
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
32020
Interpretable matrix factorization with stochasticity constrained nonnegative DEDICOM
R Sifa, C Ojeda, K Cvejoski, C Bauckhage
Proc. KDML, 2017
32017
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
22021
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