Comparing Architectures of Neural Networks for an Integration in Enterprise Systems: A Retail Case Study. - Marek Hütsch (CENTERIS/ProjMAN/HCist, 2020)

Transfer Learning to enable Flexibility of Demand Forecasting: Dropout Profiles to protect from Negative Transfer. - Marek Hütsch (ECIS, 2021)

Implementation of Placement Optimization in Electronic Commerce: Towards a Data Generation Method to Increase Forecast Elasticity. - Marek Hütsch; Tobias Wulfert (PACIS, 2021)

Design Principles for Machine Learning Marketplaces in Enterprise Systems. - Marek Hütsch; Tobias Wulfert (HICSS, 2022)

A Structured Literature Review on the Application of Machine Learning in Retail. - Marek Hütsch; Tobias Wulfert (ICEIS (1), 2022)

A Machine Learning Model Marketplace to Overcome Low Price Elasticity of Sales Forecasting. - Marek Hütsch (Wirtschaftsinformatik, 2022)

Identifying Application Areas for Machine Learning in the Retail Sector. - Clemens Brackmann; Marek Hütsch; Tobias Wulfert (SN Comput. Sci., 2023)