Christoph Molnar

2.6k total citations · 2 hit papers
12 papers, 1.0k citations indexed

About

Christoph Molnar is a scholar working on Artificial Intelligence, Statistics and Probability and Political Science and International Relations. According to data from OpenAlex, Christoph Molnar has authored 12 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Artificial Intelligence, 2 papers in Statistics and Probability and 1 paper in Political Science and International Relations. Recurrent topics in Christoph Molnar's work include Explainable Artificial Intelligence (XAI) (6 papers), Machine Learning and Data Classification (5 papers) and Bayesian Modeling and Causal Inference (2 papers). Christoph Molnar is often cited by papers focused on Explainable Artificial Intelligence (XAI) (6 papers), Machine Learning and Data Classification (5 papers) and Bayesian Modeling and Causal Inference (2 papers). Christoph Molnar collaborates with scholars based in Germany, Austria and Netherlands. Christoph Molnar's co-authors include Bernd Bischl, Gunnar König, Alexandre M.J.‐C. Wadoux, Giuseppe Casalicchio, Désirée van der Heijde, Robert Landewé, Pascale Exer, Lukas Wildi, Giorgio Tamborrini and Xenofon Baraliakos and has published in prestigious journals such as Annals of the Rheumatic Diseases, Geoderma and Data Mining and Knowledge Discovery.

In The Last Decade

Christoph Molnar

12 papers receiving 989 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

iml: An R package for Interpretable Machine Learning

2018 382 citations Christoph Molnar The Journal of Open Source Software profile →
Interpretable Machine Learning

2020 238 citations Christoph Molnar profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Christoph Molnar Germany	10	309	183	112	82	79	12	1.0k
Guo Tang China	10	70 0.2×	141 0.8×	14 0.1×	41 0.5×	40 0.5×	19	824
Søren Feodor Nielsen Denmark	14	114 0.4×	80 0.4×	26 0.2×	27 0.3×	27 0.3×	35	798
Udaya B. Kogalur United States	8	175 0.6×	14 0.1×	46 0.4×	33 0.4×	36 0.5×	8	1.0k
Samuel Müller Australia	22	348 1.1×	14 0.1×	39 0.3×	39 0.5×	49 0.6×	103	2.1k
Steven J. Rigatti United States	3	176 0.6×	15 0.1×	42 0.4×	61 0.7×	41 0.5×	12	980
Rosa Arboretti Italy	17	58 0.2×	91 0.5×	48 0.4×	24 0.3×	30 0.4×	79	1.1k
Kye Hyun Kim South Korea	20	177 0.6×	22 0.1×	43 0.4×	30 0.4×	81 1.0×	112	1.5k
Qiliang Liu China	18	91 0.3×	42 0.2×	49 0.4×	69 0.8×	86 1.1×	69	1.0k
Angelo Facchini Italy	22	50 0.2×	37 0.2×	14 0.1×	248 3.0×	103 1.3×	68	1.2k
Xiaohang Liu China	23	40 0.1×	93 0.5×	18 0.2×	182 2.2×	364 4.6×	113	1.8k

Countries citing papers authored by Christoph Molnar

Since Specialization

Citations

This map shows the geographic impact of Christoph Molnar'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 Christoph Molnar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Christoph Molnar more than expected).

Fields of papers citing papers by Christoph Molnar

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Christoph Molnar. 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 Christoph Molnar. The network helps show where Christoph Molnar may publish in the future.

Co-authorship network of co-authors of Christoph Molnar

This figure shows the co-authorship network connecting the top 25 collaborators of Christoph Molnar. A scholar is included among the top collaborators of Christoph Molnar 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 Christoph Molnar. Christoph Molnar is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

12 of 12 papers shown

1.

Casalicchio, Giuseppe, et al.. (2024). Correction: Marginal effects for non-linear prediction functions. Data Mining and Knowledge Discovery. 38(6). 4234–4235. 1 indexed citations

2.

Casalicchio, Giuseppe, et al.. (2024). Marginal effects for non-linear prediction functions. Data Mining and Knowledge Discovery. 38(5). 2997–3042. 2 indexed citations

3.

Freiesleben, Timo, Gunnar König, Christoph Molnar, & Álvaro Tejero-Cantero. (2024). Scientific Inference with Interpretable Machine Learning: Analyzing Models to Learn About Real-World Phenomena. Minds and Machines. 34(3). 9 indexed citations

4.

Molnar, Christoph, Gunnar König, Bernd Bischl, & Giuseppe Casalicchio. (2023). Model-agnostic feature importance and effects with dependent features: a conditional subgroup approach. Data Mining and Knowledge Discovery. 38(5). 2903–2941. 53 indexed citations

5.

Wadoux, Alexandre M.J.‐C. & Christoph Molnar. (2022). Beyond prediction: methods for interpreting complex models of soil variation. Geoderma. 422. 115953–115953. 49 indexed citations

6.

König, Gunnar, Christoph Molnar, Bernd Bischl, & Moritz Grosse‐Wentrup. (2021). Relative Feature Importance. 9318–9325. 39 indexed citations

7.

Molnar, Christoph. (2020). Interpretable Machine Learning. 238 indexed citations breakdown →

8.

Molnar, Christoph, Giuseppe Casalicchio, & Bernd Bischl. (2019). Quantifying Interpretability of Arbitrary Machine Learning Models Through Functional Decomposition.. arXiv (Cornell University). 9 indexed citations

9.

Molnar, Christoph. (2018). iml: An R package for Interpretable Machine Learning. The Journal of Open Source Software. 3(26). 786–786. 382 indexed citations breakdown →

10.

Molnar, Christoph, Almut Scherer, Xenofon Baraliakos, et al.. (2017). TNF blockers inhibit spinal radiographic progression in ankylosing spondylitis by reducing disease activity: results from the Swiss Clinical Quality Management cohort. Annals of the Rheumatic Diseases. 77(1). 63–69. 186 indexed citations

11.

Thurner, Paul W., et al.. (2015). Estimation of voter transitions based on ecological inference: an empirical assessment of different approaches. AStA Advances in Statistical Analysis. 100(2). 133–159. 20 indexed citations

12.

Borasio, Gian Domenico, et al.. (2012). Errors in Palliative Care: Kinds, Causes, and Consequences: A Pilot Survey of Experiences and Attitudes of Palliative Care Professionals. Journal of Palliative Medicine. 16(1). 74–81. 25 indexed citations

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.

Explore authors with similar magnitude of impact