6 citations · 7 across the 2 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★ 1 cited
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…