Publications

My google scholar profile is available here.

2026

P. Schäfer, U. Leser, M. Ceccarello. SCAMPI – Fast Pattern Discovery in Massive Time Series. SIGMOD, Huntington Beach, CA, USA, (2026).
F. Chavelli, A. Ermshaus, P. Schäfer, F. Yang, J. Paparrizos, P. Boniol. TSB-SEG: A Systematic Time-Series Segmentation Benchmark. NeurIPS, (2026, accepted).
F. Chavelli, A. Ermshaus, F. Yang, P. Schäfer, J. Paparrizos, P. Boniol. tsseg: An Interactive Toolkit for Time Series Segmentation. Demo @ ECML/PKDD, 2026.
A. Ermshaus, P. Schäfer, U. Leser. CLaP — State Detection from Time Series, PVLDB, Boston, MA, USA, 2026. Paper · Code

L. Feremans, P. Schäfer, W. Meert. MotiPlus and MotiSet: Discovering the best set of Motiflets in Time Series, ECML/PKDD 2025, Porto, Portugal. Paper
P. Schäfer, J. Brand, U. Leser, B. Peng, T. Palpanas. Fast and Exact Similarity Search in less than a Blink of an Eye, ICDE 2025, Hong Kong SAR, China. Paper · Code
P. Schäfer, U. Leser. Discovering Leitmotifs in Multidimensional Time Series, PVLDB 2025. Paper · Code · Talk
A. Ermshaus, P. Schäfer, U. Leser. CLaP — State Detection from Time Series, Preprint. Paper draft

P. Schäfer, J. Brand, U. Leser, P. Botao, T. Palpanas. Fast and Exact Similarity Search in less than a Blink of an Eye, Preprint. Paper draft · Code
M. Middlehurst, A. Ismail-Fawaz, A. Guillaume, C. Holder, D. Guijo-Rubio, G. Bulatova, L. Tsaprounis, L. Mentel, M. Walter, P. Schäfer, A. Bagnall. aeon: a Python Toolkit for Learning from Time Series, Journal of Machine Learning Research, 2024. Paper
A. Bagnall, M. Middlehurst, G. Forestier, A. Ismail-Fawaz, A. Guillaume, D. G. Rubio, A. Ermshaus, P. Schäfer, T. Papenbrock, S. Schmidl, P. Wenig. An Introduction to Machine Learning from Time Series, Tutorial @ ECML-PKDD 2024. Webpage
A. Ermshaus, P. Schäfer, U. Leser. Raising the ClaSS of Streaming Time Series Segmentation, PVLDB, Guangzhou, China, 2024. Paper · Code
M. Middlehurst, P. Schäfer, A. J. Bagnall. Bake off redux: a review and experimental evaluation of recent time series classification algorithms, Data Mining and Knowledge Discovery, 2024. Paper · Webpage

A. Ermshaus, P. Schäfer, U. Leser. ClaSP: parameter-free time series segmentation, Data Mining and Knowledge Discovery, 2023. Paper · Webpage
P. Schäfer, U. Leser. WEASEL 2.0 — A Random Dilated Dictionary Transform for Fast, Accurate and Memory Constrained Time Series Classification, Journal Track @ ECML/PKDD 2023. Paper · Code
P. Schäfer, U. Leser. Motiflets — Simple and Accurate Detection of Motifs in Time Series, PVLDB, Vancouver, Canada, 2023. Paper · Code · Talk

A. Ermshaus, P. Schäfer, U. Leser. Window Size Selection in Unsupervised Time Series Analytics: A Review and Benchmark, AALTD @ ECML/PKDD, 2022. Paper · Code

P. Schäfer, A. Ermshaus, U. Leser. ClaSP — Time Series Segmentation, CIKM 2021. Paper · Webpage · Code · Talk

P. Schäfer, U. Leser. TEASER: Early and Accurate Time Series Classification, ECML/PKDD 2020. Paper · Code · Talk

S. Sprenger, P. Schäfer, U. Leser. BB-Tree: A practical and efficient main-memory index structure for multidimensional workloads, EDBT 2019, Lisbon, Portugal. Paper
S. Sprenger, P. Schäfer, U. Leser. BB-Tree: A main-memory index structure for multidimensional range queries (short paper), ICDE 2019, Macau, China.

P. Schäfer, U. Leser. Multivariate Time Series Classification with WEASEL+MUSE, 3rd ECML/PKDD Workshop on AALTD, 2018. Code · Talk
S. Sprenger, P. Schäfer, U. Leser. Multidimensional Range Queries on Modern Hardware, Preprint. Paper
P. Schäfеr, D. Pflugmacher, P. Hostert, U. Leser. Classifying land cover from satellite images using time series analytics, EDBT/ICDT 2018 Workshops. Paper
P. Schäfer, U. Leser. Multivariate Time Series Classification with WEASEL+MUSE, Preprint. Paper · Code

P. Schäfer, U. Leser. Fast and Accurate Time Series Classification with WEASEL, CIKM 2017. Paper · Code · Talk
P. Schäfer, U. Leser. Benchmarking Univariate Time Series Classifiers, BTW 2017. Paper

P. Schäfer. Scalable Time Series Classification, ECML/PKDD 2016 & Data Mining and Knowledge Discovery 2016. Paper · Keynote · PPT · Code

P. Schäfer. Scalable Time Series Classification for Data Analytics, Dissertation 2015. Dissertation · Keynote · PPT

P. Schäfer. The BOSS is concerned with time series classification in the presence of noise, Data Mining and Knowledge Discovery 2014. Paper · Code
P. Schäfer. Experiencing the Shotgun Distance for Time Series Analysis, Transactions on Machine Learning and Data Mining 2014. Paper · Code
I. Potamitis, P. Schäfer. On classifying insects from their wing-beat: New results, Ecology and acoustics, Paris, France 2014.
P. Schäfer. Towards Time Series Classification without Human Preprocessing, MLDM 2014. Paper · Code
Jens Krüger et al. The MoSGrid science gateway – A complete solution for molecular simulations, Journal of Chemical Theory and Computation, 2014. Paper

P. Schäfer. Shooting Audio Recordings of Insects with SFA, AmiBio Workshop 2013.
P. Schäfer, S. Dressler. SFA: a symbolic Fourier approximation and index for similarity search in high dimensional datasets, EDBT 2012. Paper · Code