Nicolas Schilling
Impact in
- Signal Processing top 2%
- Time Series Analysis and Forecasting
- Music and Audio Processing
- Artificial Intelligence top 5%
- Anomaly Detection Techniques and Applications
- Machine Learning and Data Classification
- Advanced Text Analysis Techniques
- Data Stream Mining Techniques
Papers in
-
- Machine Learning and Data Classification 7
- Metaheuristic Optimization Algorithms Research 5
-
- Advanced Multi-Objective Optimization Algorithms 7
- Co-authors
- Lars Schmidt-Thieme (16 shared papers)Martin Wistuba (8 shared papers)Josif Grabocka (3 shared papers)Nghia Duong‐Trung (4 shared papers)Mit Shah (1 shared paper)M. Jungheim (1 shared paper)M. Ptok (1 shared paper)Urs F. Greber (1 shared paper)
- Journals
- ACM Transactions on Knowledge Discovery from Data (1 paper)Machine Learning (1 paper)Science Advances (1 paper)Physiology & Behavior (1 paper)Repository KITopen (Karlsruhe Institute of Technology) (2 papers)
- Partner nations
- GermanySwitzerland
In The Last Decade
Nicolas Schilling
16 papers receiving 508 citations
Nicolas Schilling's Hit Papers
Peers
Comparison fields: 5 of 76
- Signal Processing 294
- Artificial Intelligence 312
- Economics and Econometrics 93
- Computational Mathematics 2
- Management Science and Operations Research 34
Countries citing papers authored by Nicolas Schilling
This map shows the geographic impact of Nicolas Schilling's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Nicolas Schilling with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nicolas Schilling more than expected).
Fields of papers citing papers by Nicolas Schilling
This network shows the impact of papers produced by Nicolas Schilling. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Nicolas Schilling. The network helps show where Nicolas Schilling may publish in the future.
Co-authors
The 12 scholars most cited alongside Nicolas Schilling, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Learning time-series shapelets Hit paper breakdown → | 2014 | 283 |
| 2 | 2017 | 51 | |
| 3 | 2015 | 37 | |
| 4 | 2016 | 34 | |
| 5 | 2016 | 22 | |
| 6 | 2016 | 21 | |
| 7 | 2016 | 20 | |
| 8 | 2016 | 16 | |
| 9 | 2021 | 14 | |
| 10 | 2015 | 13 | |
| 11 | 2015 | 4 | |
| 12 | 2017 | 3 | |
| 13 | Learning data set similarities for hyperparameter optimization initializations | 2015 | 2 |
| 14 | Matrix Factorization for Near Real-time Geolocation Prediction in Twitter Stream. | 2016 | 1 |
| 15 | Finding Hierarchy of Topics from Twitter Data. | 2017 | 1 |
| 16 | 2018 | 1 | |
| 17 | 2018 | 0 |
About Nicolas Schilling
Nicolas Schilling is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Statistical and Nonlinear Physics, Information Systems and Computer Vision and Pattern Recognition, having authored 17 papers that have together received 523 indexed citations. Recurring topics across this work include Machine Learning and Data Classification (7 papers), Advanced Multi-Objective Optimization Algorithms (7 papers), Metaheuristic Optimization Algorithms Research (5 papers), Complex Network Analysis Techniques (4 papers), Music and Audio Processing (3 papers), Time Series Analysis and Forecasting (3 papers), Human Mobility and Location-Based Analysis (2 papers) and Peer-to-Peer Network Technologies (1 paper). The work is most often cited by research in Signal Processing (294 citations), Artificial Intelligence (312 citations), Economics and Econometrics (93 citations), Computational Mathematics (2 citations) and Management Science and Operations Research (34 citations). Nicolas Schilling has collaborated with scholars based in Germany and Switzerland. Frequent co-authors include Lars Schmidt-Thieme, Martin Wistuba, Josif Grabocka, Nghia Duong‐Trung, Mit Shah, M. Jungheim, M. Ptok, Urs F. Greber, Maarit Suomalainen and Silvio Hemmi. Their work appears in journals such as ACM Transactions on Knowledge Discovery from Data, Machine Learning, Science Advances, Physiology & Behavior and Repository KITopen (Karlsruhe Institute of Technology).
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.