6 citations · 6 across the 1 of their papers we have counts for
2 papers
stat.ML2019★ 6 cited
Deep learning for Chemometric and non-translational data
Jacob Søgaard Larsen, Line Clemmensen
We propose a novel method to train deep convolutional neural networks which learn from multiple data sets of varying input sizes through weight sharing. This is an advantage in che…
stat.ME2019
Model based Level Shift Detection in Autocorrelated Data Streams using a moving window
Jacob Søgaard Larsen, Anders Stockmarr, Bjarne Kjær Ersbøll +1
Standard Control Chart techniques to detect level shift in data streams assume independence between observations. As data today is collected with high frequency, this assumption is…