Jakob Richter
- Artificial Intelligence top 5%
- Environmental Engineering top 5%
- Ecology top 10%
- Global and Planetary Change top 10%
- Molecular Biology
- Co-authors
- Patrick SchratzMichel LangBernd BischlJannes MuenchowEugenia IturritxaAlexander BrenningStefan CoorsMartin Binder
- Topics
- Machine Learning and Data Classification (6 papers)Advanced Multi-Objective Optimization Algorithms (4 papers)Reproductive Biology and Fertility (2 papers)
- Partner nations
- GermanyUnited StatesSpain
In The Last Decade
Jakob Richter
18 papers receiving 1.3k citations
Hit Papers
Peers
Comparison fields: 5 of 176
- Artificial Intelligence 306
- Environmental Engineering 168
- Ecology 137
- Global and Planetary Change 135
- Molecular Biology 117
Countries citing papers authored by Jakob Richter
This map shows the geographic impact of Jakob Richter'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 Jakob Richter with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jakob Richter more than expected).
Fields of papers citing papers by Jakob Richter
This network shows the impact of papers produced by Jakob Richter. 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 Jakob Richter. The network helps show where Jakob Richter may publish in the future.
Co-authorship network of co-authors of Jakob Richter
This figure shows the co-authorship network connecting the top 25 collaborators of Jakob Richter. A scholar is included among the top collaborators of Jakob Richter based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Jakob Richter. Jakob Richter is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 4 | |
| 3 | 6 | |
| 4 | 5 | |
| 5 | 36 | |
| 6 | Hyperparameter optimization: Foundations, algorithms, best practices, and open challengesbreakdown → | 398 |
| 7 | 5 | |
| 8 | 5 | |
| 9 | 3 | |
| 10 | Define and Work with Parameter Spaces for Complex Algorithms [R package paradox version 0.6.0] | 1 |
| 11 | 235 | |
| 12 | Hyperparameter tuning and performance assessment of statistical and machine-learning algorithms using spatial databreakdown → | 367 |
| 13 | 3 | |
| 14 | 4 | |
| 15 | 1 | |
| 16 | Machine Learning in R | 7 |
| 17 | 37 | |
| 18 | 200 | |
| 19 | 7 |
About Jakob Richter
Jakob Richter is a scholar working on Computational Theory and Mathematics, Statistics and Probability and Reproductive Medicine, having authored 19 papers that have together received 1.3k indexed citations. Recurring topics across this work include Machine Learning and Data Classification (6 papers), Advanced Multi-Objective Optimization Algorithms (4 papers) and Reproductive Biology and Fertility (2 papers). The work is most often cited by research in Environmental Engineering (168 citations), Artificial Intelligence (306 citations) and Ecological Modeling (37 citations). Jakob Richter has collaborated with scholars based in Germany, United States and Spain. Frequent co-authors include Patrick Schratz, Michel Lang, Bernd Bischl, Jannes Muenchow, Eugenia Iturritxa, Alexander Brenning, Stefan Coors, Martin Binder, Lars Kotthoff and Giuseppe Casalicchio. Their work appears in journals such as Bioinformatics, Machine Learning and Ecological Modelling.
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.