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Louis Steinmeister
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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
212020
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
132020
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
92021
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
22020
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
12023
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
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Articles 1–8