Folgen
Timo Nolle
Timo Nolle
Telecooperation, Computer Science
Bestätigte E-Mail-Adresse bei tk.tu-darmstadt.de - Startseite
Titel
Zitiert von
Zitiert von
Jahr
Analyzing business process anomalies using autoencoders
T Nolle, S Luettgen, A Seeliger, M Mühlhäuser
Machine Learning 107, 1875-1893, 2018
942018
BINet: multivariate business process anomaly detection using deep learning
T Nolle, A Seeliger, M Mühlhäuser
International Conference on Business Process Management, 271-287, 2018
672018
Binet: Multi-perspective business process anomaly classification
T Nolle, S Luettgen, A Seeliger, M Mühlhäuser
Information Systems 103, 101458, 2022
662022
Unsupervised anomaly detection in noisy business process event logs using denoising autoencoders
T Nolle, A Seeliger, M Mühlhäuser
Discovery Science: 19th International Conference, DS 2016, Bari, Italy …, 2016
582016
Detecting concept drift in processes using graph metrics on process graphs
A Seeliger, T Nolle, M Mühlhäuser
Proceedings of the 9th Conference on Subject-Oriented Business Process …, 2017
482017
DeepAlign: alignment-based process anomaly correction using recurrent neural networks
T Nolle, A Seeliger, N Thoma, M Mühlhäuser
International conference on advanced information systems engineering, 319-333, 2020
242020
ProcessExplorer: intelligent process mining guidance
A Seeliger, A Sánchez Guinea, T Nolle, M Mühlhäuser
Business Process Management: 17th International Conference, BPM 2019, Vienna …, 2019
242019
Finding structure in the unstructured: hybrid feature set clustering for process discovery
A Seeliger, T Nolle, M Mühlhäuser
Business Process Management: 16th International Conference, BPM 2018, Sydney …, 2018
152018
Case2vec: Advances in representation learning for business processes
S Luettgen, A Seeliger, T Nolle, M Mühlhäuser
International Conference on Process Mining, 162-174, 2020
102020
Process compliance checking using taint flow analysis
A Seeliger, T Nolle, B Schmidt, M Mühlhäuser
102016
Learning of process representations using recurrent neural networks
A Seeliger, S Luettgen, T Nolle, M Mühlhäuser
International Conference on Advanced Information Systems Engineering, 109-124, 2021
92021
Process explorer: an interactive visual recommendation system for process mining
A Seeliger, T Nolle, M Mühlhäuser
KDD Workshop on Interactive Data Exploration and Analytics, 2018
72018
Data-driven detection of congestion-affected roads
T Nolle, I Schweizer, F Janssen
Technical Report TUD-KE-2014-02, 2014
52014
Capturing daily student life by recognizing complex activities using smartphones
C Meurisch, A Gogel, B Schmidt, T Nolle, F Janssen, I Schweizer, ...
Proceedings of the 14th EAI International Conference on Mobile and …, 2017
32017
Inferring a Multi-perspective Likelihood Graph from Black-Box Next Event Predictors
Y Gerlach, A Seeliger, T Nolle, M Mühlhäuser
International Conference on Advanced Information Systems Engineering, 19-35, 2022
22022
Process Explorer: Interactive Visual Exploration of Event Logs with Analysis Guidance
A Seeliger, M Ratzke, T Nolle, M Mühlhäuser
Proceedings of the 1st International Conference on Process Mining, Aachen …, 2019
22019
Process learning for autonomous process anomaly correction
T Nolle
Learning 1, P4, 2003
22003
Inferring a Multi-perspective Likelihood Graph from Black-Box Next Event Predictors
T Nolle, M Mühlhäuser
Advanced Information Systems Engineering: 34th International Conference …, 2022
2022
Extended synthetic event logs for multi-perspective trace clustering
A Seeliger, S Lüttgen, M Mühlhäuser, T Nolle
2020
Synthetic event logs for multi-perspective trace clustering
A Seeliger, T Nolle, M Mühlhäuser
2018
Das System kann den Vorgang jetzt nicht ausführen. Versuchen Sie es später erneut.
Artikel 1–20