An explainable and statistically validated ensemble clustering model applied to the identification of traumatic brain injury subgroups D Yeboah, L Steinmeister, DB Hier, B Hadi, DC Wunsch, GR Olbricht, ... IEEE Access 8, 180690-180705, 2020 | 21 | 2020 |
Joint Control of Manufacturing and Onsite Microgrid System via Novel Neural-Network Integrated Reinforcement Learning Algorithms W Hu, Z Sun, J Yang, L Steimeister, K Xu | 13 | 2020 |
Heterogeneity in blood biomarker trajectories after mild TBI revealed by unsupervised learning LA Bui, D Yeboah, L Steinmeister, S Azizi, DB Hier, DC Wunsch, ... IEEE/ACM transactions on computational biology and bioinformatics 19 (3 …, 2021 | 9 | 2021 |
Handling missing data for unsupervised learning with an application on a FITBIR Traumatic Brain Injury (TBI) Dataset L Steinmeister, D Yeboah, G Olbricht, T Oberfami-Ajayi, B Hadi, D Hier, ... Military Health System Research Symposium, 2020 | 2 | 2020 |
Testing The Limits: A Robustness Analysis Of Logistic Growth Models For Life Cycle Estimation During The COVID-19 Pandemic L Steinmeister, B Ramosaj, L Schröter, M Pauly ESSN: 2701-6277, 33-44, 2023 | 1 | 2023 |
Human Vs. Machines: Who Wins In Semiconductor Market Forecasting? L Steinmeister, M Pauly | | 2024 |
FuzzyART: An R Package for ART-based Clustering L Steinmeister, DC Wunsch II https://dx.doi.org/10.13140/RG.2.2.11823.25761, 2021 | | 2021 |
Less is more: Beating the market with recurrent reinforcement learning LKB Steinmeister Missouri University of Science and Technology, 2019 | | 2019 |