Maximilian Schleich
Impact in
- Signal Processing top 5%
- Data Management and Algorithms
Papers in
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- Advanced Database Systems and Queries 8
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- Data Management and Algorithms 10
- Co-authors
- Dan Olteanu (11 shared papers)Dan Suciu (6 shared papers)Guy Van den Broeck (2 shared papers)Radu Ciucanu (1 shared paper)Hung Q. Ngo (6 shared papers)Mahmoud Abo Khamis (5 shared papers)XuanLong Nguyen (5 shared papers)Amir Shaikhha (4 shared papers)
- Journals
- Proceedings of the VLDB Endowment (4 papers)ACM SIGMOD Record (1 paper)Journal of Artificial Intelligence Research (1 paper)Zurich Open Repository and Archive (University of Zurich) (1 paper)Proceedings of the ACM on Management of Data (2 papers)
- Partner nations
- United KingdomUnited StatesSwitzerland
In The Last Decade
Maximilian Schleich
17 papers receiving 589 citations
Maximilian Schleich's Hit Papers
Peers
Comparison fields: 5 of 111
- Computational Mathematics 8
- Signal Processing 123
- Information Systems and Management 60
- Artificial Intelligence 266
- Computer Networks and Communications 184
Countries citing papers authored by Maximilian Schleich
This map shows the geographic impact of Maximilian Schleich'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 Maximilian Schleich with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Maximilian Schleich more than expected).
Fields of papers citing papers by Maximilian Schleich
This network shows the impact of papers produced by Maximilian Schleich. 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 Maximilian Schleich. The network helps show where Maximilian Schleich may publish in the future.
Co-authors
The 10 scholars most cited alongside Maximilian Schleich, 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 | On the Tractability of SHAP Explanations Hit paper breakdown → | 2022 | 248 |
| 2 | 2016 | 89 | |
| 3 | 2016 | 43 | |
| 4 | 2019 | 34 | |
| 5 | 2018 | 32 | |
| 6 | 2021 | 31 | |
| 7 | 2018 | 31 | |
| 8 | 2021 | 23 | |
| 9 | 2023 | 14 | |
| 10 | 2016 | 14 | |
| 11 | 2020 | 10 | |
| 12 | 2019 | 9 | |
| 13 | 2021 | 8 | |
| 14 | 2022 | 4 | |
| 15 | In-Database Learning with Sparse Tensors | 2017 | 3 |
| 16 | 2024 | 2 | |
| 17 | In-Database Factorized Learning. | 2017 | 1 |
About Maximilian Schleich
Maximilian Schleich is a scholar working on Computer Networks and Communications, Signal Processing, Artificial Intelligence, Information Systems and Management and Computer Vision and Pattern Recognition, having authored 17 papers that have together received 596 indexed citations. Recurring topics across this work include Data Management and Algorithms (10 papers), Advanced Database Systems and Queries (8 papers), Bayesian Modeling and Causal Inference (4 papers), Explainable Artificial Intelligence (XAI) (4 papers), Machine Learning and Data Classification (3 papers), Scientific Computing and Data Management (3 papers), Parallel Computing and Optimization Techniques (2 papers) and Data Quality and Management (2 papers). The work is most often cited by research in Computational Mathematics (8 citations), Signal Processing (123 citations), Information Systems and Management (60 citations), Artificial Intelligence (266 citations) and Computer Networks and Communications (184 citations). Maximilian Schleich has collaborated with scholars based in United Kingdom, United States and Switzerland. Frequent co-authors include Dan Olteanu, Dan Suciu, Guy Van den Broeck, Radu Ciucanu, Hung Q. Ngo, Mahmoud Abo Khamis, XuanLong Nguyen, Amir Shaikhha, Benjamin Moseley and Ryan R. Curtin. Their work appears in journals such as Proceedings of the VLDB Endowment, ACM SIGMOD Record, Journal of Artificial Intelligence Research, Zurich Open Repository and Archive (University of Zurich) and Proceedings of the ACM on Management of Data.
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.