80 citations · 179 across the 16 of their papers we have counts for
Showing 2023 · cs.LGShow all
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cs.LG2023
On the improvement of model-predictive controllers
L. Féret, A. Gepperth, S. Lambeck
This article investigates synthetic model-predictive control (MPC) problems to demonstrate that an increased precision of the internal prediction model (PM) automatially entails an…
cs.LG2023
Large-scale gradient-based training of Mixtures of Factor Analyzers
Alexander Gepperth
Gaussian Mixture Models (GMMs) are a standard tool in data analysis. However, they face problems when applied to high-dimensional data (e.g., images) due to the size of the require…
cs.LG2023★ 2 cited
Adiabatic replay for continual learning
Alexander Krawczyk, Alexander Gepperth
Conventional replay-based approaches to continual learning (CL) require, for each learning phase with new data, the replay of samples representing all of the previously learned kno…