Total spiking probability edges: a cross-correlation based method for effective connectivity estimation of cortical spiking neurons S De Blasi, M Ciba, A Bahmer, C Thielemann Journal of neuroscience methods 312, 169-181, 2019 | 21 | 2019 |
KIcker: An Industrial Drive and Control Foosball System automated with Deep Reinforcement Learning S De Blasi, S Klöser, A Müller, R Reuben, F Sturm, T Zerrer J Intell Robot Syst 102, 2021 | 10 | 2021 |
Next generation control units simplifying industrial machine learning S De Blasi, E Engels 2020 IEEE 29th International Symposium on Industrial Electronics (ISIE), 468-473, 2020 | 9 | 2020 |
Active learning approach for safe process parameter tuning S De Blasi Machine Learning, Optimization, and Data Science: 5th International …, 2019 | 7 | 2019 |
SASBO: Self-Adapting Safe Bayesian Optimization S De Blasi, A Gepperth International Conference on Machine Learning and Applications, 2020 | 6 | 2020 |
Simulation of Large Scale Neural Networks for Evaluation Applications S De Blasi POSTER 2018, 22nd International Student Conference on Electrical Engineering, 2018 | 5 | 2018 |
Safe contextual Bayesian optimization integrated in industrial control for self-learning machines S De Blasi, M Bahrami, E Engels, A Gepperth Journal of Intelligent Manufacturing 35 (2), 885-903, 2024 | 3 | 2024 |
Multi-pronged safe bayesian optimization for high dimensions S De Blasi, A Neifer, A Gepperth 2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC …, 2021 | 3 | 2021 |
Connectivity estimation of high dimensional data recorded from neuronal cells S De Blasi UAS Aschaffenburg, 2018 | 1 | 2018 |
Machine Learning for Industrial Process Optimization S De Blasi | | 2022 |