Research Areas

The focus of our research is on scalable techniques for data management and analytics. Our work targets at the synthesis of conceptual research results with prototypical deployments in different domains. Our current topics include the efficient detection of unexpected and statistically outstanding data objects, techniques that hide different kinds of person-related information in large data sets, intelligent processing of data from sensor networks and technology for modeling and execution of secure and compliant data-aware processes. We are always interested in collaborating with users as well as with researchers from other disciplines.

Publikationen


2024
A graph database for feature characterization of dislocation networks
Katzer, B.; Betsche, D.; Böhm, K.; Weygand, D.; Schulz, K.
2024. Scripta Materialia, 240, Art.-Nr.: 115841. doi:10.1016/j.scriptamat.2023.115841Full textFull text of the publication as PDF document
Adaptive Bernstein change detector for high-dimensional data streams
Heyden, M.; Fouché, E.; Arzamasov, V.; Fenn, T.; Kalinke, F.; Böhm, K.
2024. Data Mining and Knowledge Discovery, 38 (3), 1334–1363. doi:10.1007/s10618-023-00999-5Full textFull text of the publication as PDF document
Towards a Temporal Graph Query Language for Durable Patterns
Betsche, D.; Katzer, B.; Schulz, K.; Böhm, K.
2024. SSDBM ’24: Proceedings of the 36th International Conference on Scientific and Statistical Database Management, Rennes, 10th-112th July 2024, 1–4, Association for Computing Machinery (ACM). doi:10.1145/3676288.3676303Full textFull text of the publication as PDF document
Nyström Kernel Stein Discrepancy
Kalinke, F.; Szabo, Z.; Skriperumbudur, B. K.
2024. arxiv. doi:10.48550/arXiv.2406.08401
Knowledge-Guided Learning of Temporal Dynamics and its Application to Gas Turbines
Bielski, P.; Eismont, A.; Bach, J.; Leiser, F.; Kottonau, D.; Böhm, K.
2024. 15th ACM International Conference on Future and Sustainable Energy Systems, Singapur, 4th-7th June 2024, 279–290, Association for Computing Machinery (ACM). doi:10.1145/3632775.3661967Full textFull text of the publication as PDF document
Combining simulation and experimental data via surrogate modelling of continuum dislocation dynamics simulations
Katzer, B.; Betsche, D.; von Hoegen, F.; Jochum, B.; Böhm, K.; Schulz, K.
2024. Modelling and Simulation in Materials Science and Engineering, 32 (5), Art.-Nr.: 055026. doi:10.1088/1361-651X/ad4b4cFull textFull text of the publication as PDF document
DEAL: Data-Efficient Active Learning for Regression Under Drift
Böhnke, B. H.; Fouché, E.; Böhm, K.
2024. Advances in Knowledge Discovery and Data Mining : 28th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2024, Taipei, Taiwan, May 7–10, 2024, Proceedings, Part VI. Ed.: D.-N. Yang, 188 – 200, Springer Nature Singapore. doi:10.1007/978-981-97-2266-2_15
2023
Nyström -Hilbert-Schmidt Independence Criterion
Kalinke, F.; Szabó, Z.
2023. Proceedings of the Thirty-Ninth Conference on Uncertainty in Artificial Intelligence, UAI 2023, 1005 – 1015, Machine Learning Research Press (ML Research Press)
Active Learning for SAT Solver Benchmarking
Fuchs, T.; Bach, J.; Iser, M.
2023. Tools and Algorithms for the Construction and Analysis of Systems. Ed.: S. Sankaranarayanan. Pt. 1, 407–425, Springer Nature Switzerland. doi:10.1007/978-3-031-30823-9_21Full textFull text of the publication as PDF document
Multi-kernel Times Series Outlier Detection
Kalinke, F.; Fouché, E.; Thiessen, H.; Böhm, K.
2023. Discovery Science. DS 2023. Eds.: A. Bifet, A.C. Lorena, R.P. Ribeiro, J. Gama, P.H. Abreu, 688 – 702, Springer Nature Switzerland. doi:10.1007/978-3-031-45275-8_46
Reduction of data-value-aware process models: A relevance-based approach
Ordoni, E.; Mülle, J.; Böhm, K.
2023. Information Systems, 114, Art.Nr. 102157. doi:10.1016/j.is.2022.102157
A benchmark of categorical encoders for binary classification
Matteucci, F.; Arzamasov, V.; Böhm, K.
2023. A. Oh, T. Naumann, A. Globerson, K. Saenko, M. Hardt & S. Levine (Eds.), Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, NeurIPS 2023, New Orleans, LA, USA, December 10 - 16, 2023 Hrsg.: Oh, Alice; Naumann, Tristan; Globerson, Amir; Saenko, Kate; Hardt, Moritz; Levine, Sergey, PMLR
2022
Efficient SVDD sampling with approximation guarantees for the decision boundary
Englhardt, A.; Trittenbach, H.; Kottke, D.; Sick, B.; Böhm, K.
2022. Machine Learning, 111 (4), 1349–1375. doi:10.1007/s10994-022-06149-0Full textFull text of the publication as PDF document
Swellfish privacy: Supporting time-dependent relevance for continuous differential privacy
Tex, C.; Schäler, M.; Böhm, K.
2022. Information Systems, 109, Art.-Nr.: 102079. doi:10.1016/j.is.2022.102079
Tandem Outlier Detectors for Decentralized Data
Heyden, M.; Wilwer, J.; Fouché, E.; Thoma, S.; Matthiesen, S.; Gwosch, T.
2022. Proceedings of the 34th International Conference on Scientific and Statistical Database Management, Article: 25, Association for Computing Machinery (ACM). doi:10.1145/3538712.3538748Full textFull text of the publication as PDF document
An Empirical Evaluation of Constrained Feature Selection
Bach, J.; Zoller, K.; Trittenbach, H.; Schulz, K.; Böhm, K.
2022. SN Computer Science, 3 (6), Art.-Nr.: 445. doi:10.1007/s42979-022-01338-zFull textFull text of the publication as PDF document
Establishing trajectories of moving objects without identities: The intricacies of cell tracking and a solution
Cazzolato, M. T.; Traina, A. J. M.; Böhm, K.
2022. Information Systems, 105, Art.-Nr.: 101955. doi:10.1016/j.is.2021.101955
Results from the Verification of Models of Spectrum Auctions
Ordoni, E.; Mülle, J.; Böhm, K.
2022. Business Modeling and Software Design – 12th International Symposium, BMSD 2022, Fribourg, Switzerland, June 27–29, 2022, Proceedings, 54–68, Springer International Publishing. doi:10.1007/978-3-031-11510-3_4
Leveraging Constraints for User-Centric Selection of Predictive Features
Bach, J.
2022, October 6. AI Hub @ Karlsruhe (2022), Karlsruhe, Germany, October 5–7, 2022 Full textFull text of the publication as PDF document
Presentation for the Paper "A Comprehensive Study of k-Portfolios of Recent SAT Solvers"
Bach, J.
2022, August 2. 25th International Conference on Theory and Applications of Satisfiability Testing (SAT 2022), Haifa, Israel, August 2–5, 2022 Full textFull text of the publication as PDF document
2021
An overview and a benchmark of active learning for outlier detection with one-class classifiers
Trittenbach, H.; Englhardt, A.; Böhm, K.
2021. Expert systems with applications, 168, Art. Nr.: 114372. doi:10.1016/j.eswa.2020.114372
An Evaluation of NILM Approaches on Industrial Energy-Consumption Data
Kalinke, F.; Bielski, P.; Singh, S.; Fouché, E.; Böhm, K.
2021. e-Energy ’21: Proceedings of the Twelfth ACM International Conference on Future Energy Systems, 239–243, Association for Computing Machinery (ACM). doi:10.1145/3447555.3464863
Benchmarking Unsupervised Outlier Detection with Realistic Synthetic Data
Steinbuss, G.; Böhm, K.
2021. ACM Transactions on Knowledge Discovery from Data, 15 (4), Art.-Nr.: 3441453. doi:10.1145/3441453
Generating artificial outliers in the absence of genuine ones - A survey
Steinbuss, G.; Böhm, K.
2021. ACM Transactions on Knowledge Discovery from Data, 15 (2), Art.-Nr.: 30. doi:10.1145/3447822
How meaningful are similarities in deep trajectory representations?
Taghizadeh, S.; Elekes, A.; Schäler, M.; Böhm, K.
2021. Information systems, 98, Article: 101452. doi:10.1016/j.is.2019.101452
Efficient subspace search in data streams
Fouché, E.; Kalinke, F.; Böhm, K.
2021. Information systems, 97, Art.-Nr. 101705. doi:10.1016/j.is.2020.101705
Preserving secrecy in mobile social networks
Suntaxi, G.; El Ghazi, A. A.; Böhm, K.
2021. ACM Transactions on Cyber-Physical Systems, 5 (1), 5. doi:10.1145/3396071
Scalable and data-aware SQL query recommendations
Arzamasova, N.; Böhm, K.
2021. Information systems, 96, Art.-Nr.: 101646. doi:10.1016/j.is.2020.101646
A framework for dependency estimation in heterogeneous data streams
Fouché, E.; Mazankiewicz, A.; Kalinke, F.; Böhm, K.
2021. Distributed and parallel databases, 39, 415–444. doi:10.1007/s10619-020-07295-xFull textFull text of the publication as PDF document
REDS: Rule Extraction for Discovering Scenarios
Arzamasov, V.; Böhm, K.
2021. SIGMOD/PODS ’21: Proceedings of the 2021 International Conference on Management of Data: June 20-25, 2021, Virtual Event China, 115–128, Association for Computing Machinery (ACM). doi:10.1145/3448016.3457301
An ensemble technique for better decisions based on data streams and its application to data privacy
Laforet, F.; Olms, C.; Biczok, R.; Böhm, K.
2021. IEEE Transactions on Knowledge and Data Engineering, 33 (12), 3662–3674. doi:10.1109/TKDE.2020.2977035
Accurate Cardinality Estimation of Co-occurring Words Using Suffix Trees
Willkomm, J.; Schäler, M.; Böhm, K.
2021. Database Systems for Advanced Applications – 26th International Conference, DASFAA 2021, Taipei, Taiwan, April 11–14, 2021, Proceedings, Part II. Ed.: C. Jensen, 721–737, Springer International Publishing. doi:10.1007/978-3-030-73197-7_50
2020
Data-driven exploration and continuum modeling of dislocation networks
Sudmanns, M.; Bach, J.; Weygand, D.; Schulz, K.
2020. Modelling and simulation in materials science and engineering, 28 (6), Art. Nr.: 065001. doi:10.1088/1361-651X/ab97efFull textFull text of the publication as PDF document
On the Usefulness of SQL-Query-Similarity Measures to Find User Interests
Arzamasova, N.; Bohm, K.; Goldman, B.; Saaler, C.; Schaler, M.
2020. IEEE transactions on knowledge and data engineering, 32 (10), 1982–1999. doi:10.1109/TKDE.2019.2913381Full textFull text of the publication as PDF document
Active Learning of SVDD Hyperparameter Values
Trittenbach, H.; Böhm, K.; Assent, I.
2020. 2020 IEEE 7th International Conference on Data Science and Advanced Analytics: 6-9 Ocotber 2020, Sydney, Australia. Ed.: G. Webb, 109–117, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/DSAA49011.2020.00023
Finding the sweet spot: Batch selection for one-class active learning
Englhardt, A.; Trittenbach, H.; Vetter, D.; Böhm, K.
2020. Proceedings of the 2020 SIAM International Conference on Data Mining. Ed.: C. Demeniconi, 118–126, SIAM. doi:10.1137/1.9781611976236.14
Assistance system for an automated log-quality and assortment estimation based on data-driven approaches using hydraulic signals of forestry machines
Geiger, C.; Maier, N.; Kalinke, F.; Geimer, M.
2020. Fluid Power Future Technology! Vol. 3, 83–92, Technische Universität Dresden (TU Dresden). doi:10.25368/2020.97Full textFull text of the publication as PDF document
Improving semantic change analysis by combining word embeddings and word frequencies
Englhardt, A.; Willkomm, J.; Schäler, M.; Böhm, K.
2020. International journal on digital libraries, 21 (3), 247–264. doi:10.1007/s00799-019-00271-6
Privacy Measures and Storage Technologies for Battery-Based Load Hiding - an Overview and Experimental Study
Arzamasov, V.; Schwerdt, R.; Karrari, S.; Böhm, K.; Nguyen, T. B.
2020. e-Energy ’20: Proceedings of the Eleventh ACM International Conference on Future Energy Systems, Melbourne, Australia, 22 - 26 June 2020, 178–195, Association for Computing Machinery (ACM). doi:10.1145/3396851.3398320
Mining text outliers in document directories
Fouché, E.; Meng, Y.; Guo, F.; Zhuang, H.; Böhm, K.; Han, J.
2020. Proceedings 20th IEEE International Conference on Data Mining: 17-20 November 2020, Virtual Conference. Ed.: C. Plant, 152–161, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ICDM50108.2020.00024
Verification of Data-Value-Aware Processes and a Case Study on Spectrum Auctions
Ordoni, E.; Mulle, J.; Bohm, K.
2020. 2020 IEEE 22nd Conference on Business Informatics (CBI), 22 - 24 June 2020, Antwerp, Belgium, Belgium, 181–190, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/CBI49978.2020.00027
A Data-driven Approach for Estimating Relative Voltage Sensitivity
Karrari, S.; Vollmer, M.; Carne, G.; Noe, M.; Böhm, K.; Geisbüsch, J.
2020. IEEE Power & Energy Society General Meeting (PESGM 2020), 1–5, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/PESGM41954.2020.9281859Full textFull text of the publication as PDF document
Exploring the unknown – Query synthesis in one-class active learning
Englhardt, A.; Böhm, K.
2020. Proceedings of the 2020 SIAM International Conference on Data Mining. Ed.: C. Demeniconi, 145–153, SIAM. doi:10.1137/1.9781611976236.17
2019
Scaling multi-armed bandit algorithms
Fouché, E.; Komiyama, J.; Böhm, K.
2019. 25th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2019; Anchorage; United States; 4 August 2019 through 8 August 2019, 1449–1459, Association for Computing Machinery (ACM). doi:10.1145/3292500.3330862
Reducing energy time series for energy system models via self-organizing maps
Yilmaz, H. Ü.; Fouché, E.; Dengiz, T.; Krauß, L.; Keles, D.; Fichtner, W.
2019. Information technology, 61 (2-3), 125–133. doi:10.1515/itit-2019-0025
FOBSS: Monitoring data from a modular battery system
Steinbuss, G.; Rzepka, B.; Bischof, S.; Blank, T.; Böhm, K.
2019. Proceedings of the Tenth ACM International Conference on Future Energy Systems - e-Energy ’19, Phoenix, AZ, USA, June 25 - 28, 2019, 456–459, Association for Computing Machinery (ACM). doi:10.1145/3307772.3331020
A practical data-flow verification scheme for business processes
Mülle, J.; Tex, C.; Böhm, K.
2019. Information systems, 81, 136–151. doi:10.1016/j.is.2018.12.002
One-class active learning for outlier detection with multiple subspaces
Trittenbach, H.; Böhm, K.
2019. CIKM ’19 Proceedings of the 28th ACM International Conference on Information and Knowledge Management, Beijing, China, November 3-7, 2019, 811–820, Association for Computing Machinery (ACM). doi:10.1145/3357384.3357873
Learning from few samples: Lexical substitution with word embeddings for short text classification
Elekes, Á.; Di Stefano, A. S.; Schäler, M.; Böhm, K.; Keller, M.
2019. 19th ACM/IEEE Joint Conference on Digital Libraries, JCDL 2019; Urbana-Champaign; United States; 2 June 2019 through 6 June 2019. Ed.: M. Bonn, 111–119, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/JCDL.2019.00025
Unsupervised Artificial Neural Networks for Outlier Detection in High-Dimensional Data
Popovic, D.; Fouché, E.; Böhm, K.
2019. Advances in Databases and Information Systems: 23rd European Conference, ADBIS 2019, Bled, Slovenia, September 8–11, 2019, Proceedings. Ed.: T. Welzer, 3–19, Springer. doi:10.1007/978-3-030-28730-6_1
Validating one-class active learning with user studies – A prototype and open challenges
Trittenbach, H.; Englhardt, A.; Böhm, K.
2019. IAL 2019 Interactive Adaptive Learning: Proceedings of the Workshop on Interactive Adaptive Learning co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2019), Würzburg, Germany, September 16th, 2019. Ed.: D. Kottke, 17–31 Full textFull text of the publication as PDF document
Efficient Interval-focused Similarity Search under Dynamic Time Warping
Willkomm, J.; Bettinger, J.; Schäler, M.; Böhm, K.
2019. Proceedings of the 16th International Symposium on Spatial and Temporal Databases - SSTD ’19, 130–139, Association for Computing Machinery (ACM). doi:10.1145/3340964.3340969
The Effect of Temporal Aggregation on Battery Sizing for Peak Shaving
Werle, D.; Warzel, D.; Bischof, S.; Koziolek, A.; Trittenbach, H.; Böhm, K.
2019. Tenth ACM International Conference on Future Energy Systems (ACM e-Energy) and its co-located workshops, Phoenix, AZ, United States, 25th - 28th of June 2019, 482–485, Association for Computing Machinery (ACM). doi:10.1145/3307772.3331023
Iterative estimation of mutual information with error bounds
Vollmer, M.; Böhm, K.
2019. 22nd International Conference on Extending Database Technology, EDBT 2019; Lisbon; Portugal; 26 March 2019 through 29 March 2019. Ed.: Z. Kaoudi, 73–84, OpenProceedings.org. doi:10.5441/002/edbt.2019.08Full textFull text of the publication as PDF document
Understanding the effects of temporal energy-data aggregation on clustering quality
Trittenbach, H.; Bach, J.; Böhm, K.
2019. Information technology, 61 (2-3), 111–123. doi:10.1515/itit-2019-0014
Data-driven crack assessment based on surface measurements
Schulz, K.; Kreis, S.; Trittenbach, H.; Böhm, K.
2019. Engineering fracture mechanics, 218, Article no: 106552. doi:10.1016/j.engfracmech.2019.106552
Energy Time-Series Features for Emerging Applications on the Basis of Human-Readable Machine Descriptions
Vollmer, M.; Englhardt, A.; Trittenbach, H.; Bielski, P.; Karrari, S.; Böhm, K.
2019. Tenth ACM International Conference on Future Energy Systems (ACM e-Energy) and its co-located workshops, Phoenix, AZ, United States, 25th - 28th of June 2019, 474–481, Association for Computing Machinery (ACM). doi:10.1145/3307772.3331022
High-resolution Industrial Production Energy (HIPE), Version 1.0.1
Bischof, S.; Trittenbach, H.; Werle, D.; Blank, T.; Böhm, K.
2019, May 1. doi:10.5281/zenodo.14054902
Active Learning of SVDD Hyperparameter Values
Trittenbach, H.; Böhm, K.; Assent, I.
2019
On Preserving Secrecy in Mobile Social Networks
Suntaxi, G.; El Ghazi, A. A.; Böhm, K.
2019. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000096955/v2Full textFull text of the publication as PDF document
Frequent Observations from a Battery System with Subunits
Steinbuß, G.; Rzepka, B.; Bischof, S.; Blank, T.; Böhm, K.
2019. doi:10.5445/IR/1000094469
On the Usefulness of SQL-Query-Similarity Measures to Find User Interests
Arzamasova, N.; Böhm, K.; Goldman, B.; Saaler, C.; Schäler, M.
2019. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000093761Full textFull text of the publication as PDF document
2018
Towards Concise Models of Grid Stability
Arzamasov, V.; Böhm, K.; Jochem, P. E. P.
2018. 2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids, SmartGridComm 2018; Aalborg; Denmark; 29 October 2018 through 31 October 2018, Art. Nr.: 8587498, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/SmartGridComm.2018.8587498
HIPE – An energy-Status-Data set from industrial production
Bischof, S.; Trittenbach, H.; Vollmer, M.; Werle, D.; Blank, T.; Böhm, K.
2018. 9th ACM International Conference on Future Energy Systems, e-Energy 2018; Karlsruhe; Germany; 12 June 2018 through 15 June 2018, 599–603, Association for Computing Machinery (ACM). doi:10.1145/3208903.3210278
Cleaning Antipatterns in an SQL Query Log
Arzamasova, N.; Schaler, M.; Bohm, K.
2018. IEEE transactions on knowledge and data engineering, 30 (3), 421–434. doi:10.1109/TKDE.2017.2772252
Dimension-based subspace search for outlier detection
Trittenbach, H.; Böhm, K.
2018. International Journal of Data Science and Analytics. doi:10.1007/s41060-018-0137-7
Towards Meaningful Distance-preserving Encryption
Tex, C.; Schäler, M.; Böhm, K.
2018. 30th International Conference on Scientific and Statistical Database Management (SSDBM), Bozen-Bolzano, Italy, July 9 - 11, 2018, Artikel-Nr.: 2/1–12, Association for Computing Machinery (ACM). doi:10.1145/3221269.3223029
In-database analytics with ibmdbpy
Fouché, E.; Eckert, A.; Böhm, K.
2018. 30th International Conference on Scientific and Statistical Database Management, SSDBM 2018; Bolzano-Bozen; Italy; 9 July 2018 through 11 July 2018. Ed.: M. Bohlen, Art. Nr.: 31, Association for Computing Machinery (ACM). doi:10.1145/3221269.3223026
PrivEnergy – A privacy operator framework addressing individual concerns
Tex, C.; Hertweck, P.; Schäler, M.; Böhm, K.
2018. 9th ACM International Conference on Future Energy Systems, e-Energy 2018; Karlsruhe; Germany; 12 June 2018 through 15 June 2018, 426–428, Association for Computing Machinery (ACM). doi:10.1145/3208903.3212048
On the tradeoff between energy data aggregation and clustering quality
Trittenbach, H.; Bach, J.; Böhm, K.
2018. 9th ACM International Conference on Future Energy Systems, e-Energy 2018; Karlsruhe; Germany; 12 June 2018 through 15 June 2018, 399–401, Association for Computing Machinery (ACM). doi:10.1145/3208903.3212038
Distance-based data mining over encrypted data
Tex, C.; Schäler, M.; Böhm, K.
2018. Proceedings of the 34th IEEE International Conference on Data Engineering, Paris, F, 16-19 avril 2018, 1264–1267, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ICDE.2018.00126Full textFull text of the publication as PDF document
Towards Simulation-Data Science : A Case Study on Material Failures
Trittenbach, H.; Gauch, M.; Böhm, K.; Schulz, K.
2018. IEEE 5th International Conference on Data Science and Advanced Analytics (DSAA), Turin, Italy, 1-3 Oct. 2018, 450–459, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/DSAA.2018.00058
Efficient and Reliable Estimation of Cell Positions
Cazzolato, M. T.; Traina, A. J. M.; Böhm, K.
2018. 27th ACM International Conference on Information and Knowledge Management, CIKM 2018; Torino; Italy; 22 October 2018 through 26 October 2018. Ed.: N. Paton, 1043–1052, Association for Computing Machinery (ACM). doi:10.1145/3269206.3271734
A Query Algebra for Temporal Text Corpora
Willkomm, J.; Schmidt-Petri, C.; Schäler, M.; Schefczyk, M.; Böhm, K.
2018. Proceedings of the 18th ACM/IEEE on Joint Conference on Digital Libraries, Fort Worth, TX, June 3-7, 2018, 183–192, Association for Computing Machinery (ACM). doi:10.1145/3197026.3197044
Beweisbare Privatheitsgarantien durch den Einsatz wiederaufladbarer Energiespeicher
Laforet, F.; Buchmann, E.; Böhm, K.
2018. Ideen und Innovationen für die Energie von morgen : Wissenschaftliche Beiträge des KIT zu den Jahrestagungen 2014, 2016 und 2017 des KIT-Zentrums Energie. Hrsg.: W. Breh, 43–44, KIT Scientific Publishing. doi:10.5445/IR/1000085362Full textFull text of the publication as PDF document
An Overview and a Benchmark of Active Learning for One-Class Classification
Trittenbach, H.; Englhardt, A.; Böhm, K.
2018. arXiv preprint 1808.04759
On the Tradeoff between Energy Data Aggregation and Clustering Quality
Trittenbach, H.; Bach, J.; Böhm, K.
2018. 9th ACM International Conference on Future Energy Systems (e-Energy 2018), Karlsruhe, Germany, June 12–15, 2018 Full textFull text of the publication as PDF document
HIPE -- An Energy-Status-Data Set from Industrial Production
Bischof, S.; Trittenbach, H.; Vollmer, M.; Werle, D.; Blank, T.; Böhm, K.
2018. International Workshop on Energy Data and Analytics (EDA 2018), Karlsruhe, Germany, June 12, 2018
Comparing Predictions of Object Movements
Taghizadeh, S.; Schäler, M.; Böhm, K.
2018. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000081005Full textFull text of the publication as PDF document
Towards Simulation-Data Science : A Case Study on Material Failures
Trittenbach, H.; Gauch, M.; Böhm, K.; Schulz, K.
2018. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000079420Full textFull text of the publication as PDF document