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researcher

Johannes Lahann

2 papers hereh-index 7396 citations17 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author2

Across the 2 of 2 papers where every author was matched, so the position is known.

fields
  • cs.LG2

identity via Semantic Scholar / OpenAlex

most citedA systematic literature review on state-of-the-art deep learning methods for process prediction

147 citations · 147 across the 2 of their papers we have counts for

collaborators

2 papers

cs.LG2021

Multivariate Business Process Representation Learning utilizing Gramian Angular Fields and Convolutional Neural Networks

Peter Pfeiffer, Johannes Lahann, Peter Fettke

Learning meaningful representations of data is an important aspect of machine learning and has recently been successfully applied to many domains like language understanding or com…

cs.LG2021★ 147 cited

A systematic literature review on state-of-the-art deep learning methods for process prediction

Dominic A. Neu, Johannes Lahann, Peter Fettke

Process mining enables the reconstruction and evaluation of business processes based on digital traces in IT systems. An increasingly important technique in this context is process…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.