Anton Schwaighofer

2.4k total citations
36 papers, 1.3k citations indexed

About

Anton Schwaighofer is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Anton Schwaighofer has authored 36 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Artificial Intelligence, 6 papers in Computational Theory and Mathematics and 6 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Anton Schwaighofer's work include Computational Drug Discovery Methods (6 papers), Gaussian Processes and Bayesian Inference (6 papers) and Analytical Chemistry and Chromatography (5 papers). Anton Schwaighofer is often cited by papers focused on Computational Drug Discovery Methods (6 papers), Gaussian Processes and Bayesian Inference (6 papers) and Analytical Chemistry and Chromatography (5 papers). Anton Schwaighofer collaborates with scholars based in Germany, United States and Austria. Anton Schwaighofer's co-authors include Volker Tresp, Kai Yu, H.-P. Kriegel, Xiaowei Xu, Kai Yu, Sebastian Mika, Timon Schroeter, Nikolaus Heinrich, Klaus‐Robert Müller and Antonius ter Laak and has published in prestigious journals such as Nature Communications, IEEE Transactions on Biomedical Engineering and IEEE Transactions on Knowledge and Data Engineering.

In The Last Decade

Anton Schwaighofer

36 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Anton Schwaighofer Germany	18	577	255	246	229	136	36	1.3k
Monica Bianchini Italy	20	762 1.3×	168 0.7×	441 1.8×	227 1.0×	170 1.3×	84	1.9k
Zhijie Wang China	13	313 0.5×	221 0.9×	304 1.2×	69 0.3×	179 1.3×	52	993
Stefanie Jegelka United States	18	657 1.1×	265 1.0×	488 2.0×	68 0.3×	66 0.5×	73	1.4k
Jakub M. Tomczak Netherlands	16	541 0.9×	160 0.6×	260 1.1×	54 0.2×	143 1.1×	47	1.2k
Kangshun Li China	21	760 1.3×	402 1.6×	290 1.2×	113 0.5×	203 1.5×	128	1.8k
Zakariya Yahya Algamal Iraq	28	692 1.2×	367 1.4×	244 1.0×	63 0.3×	414 3.0×	157	2.2k
Lei Xiao China	24	745 1.3×	97 0.4×	165 0.7×	107 0.5×	176 1.3×	156	2.2k
Yingce Xia China	20	985 1.7×	169 0.7×	383 1.6×	47 0.2×	287 2.1×	56	1.5k
Sen Yang China	15	770 1.3×	327 1.3×	381 1.5×	129 0.6×	359 2.6×	60	1.5k
Tengfei Ma China	21	857 1.5×	472 1.9×	180 0.7×	144 0.6×	538 4.0×	96	1.7k

Countries citing papers authored by Anton Schwaighofer

Since Specialization

Citations

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

Fields of papers citing papers by Anton Schwaighofer

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Anton Schwaighofer

This figure shows the co-authorship network connecting the top 25 collaborators of Anton Schwaighofer. A scholar is included among the top collaborators of Anton Schwaighofer 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 Anton Schwaighofer. Anton Schwaighofer 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:

20 of 20 papers shown

1.

Pérez‐García, Fernando, Shruthi Bannur, Daniel C. Castro, et al.. (2024). MAIRA at RRG24: A specialised large multimodal model for radiology report generation. 597–602. 4 indexed citations

2.

Liu, Qianchu, Stephanie L. Hyland, Shruthi Bannur, et al.. (2023). Exploring the Boundaries of GPT-4 in Radiology. 14414–14445. 14 indexed citations

3.

Castro, Daniel C., Ryutaro Tanno, Anton Schwaighofer, et al.. (2022). Active label cleaning for improved dataset quality under resource constraints. Nature Communications. 13(1). 1161–1161. 55 indexed citations

4.

Yu, Kai, et al.. (2012). Collaborative Ensemble Learning: Combining Collaborative and Content-Based Information Filtering via Hierarchical Bayes. arXiv (Cornell University). 616–623. 19 indexed citations

5.

Quiñonero-Candela, Joaquin, Masashi Sugiyama, Anton Schwaighofer, & Neil D. Lawrence. (2009). Theoretical Views on Dataset and Covariate Shift. 39–39. 1 indexed citations

6.

Quiñonero-Candela, Joaquin, Masashi Sugiyama, Anton Schwaighofer, & Neil D. Lawrence. (2009). Geometry of Covariate Shift with Applications to Active Learning. 87–105. 7 indexed citations

7.

Quiñonero-Candela, Joaquin, Masashi Sugiyama, Anton Schwaighofer, & Neil D. Lawrence. (2009). Binary Classification under Sample Selection Bias. 41–64. 4 indexed citations

8.

Schwaighofer, Anton, Timon Schroeter, Sebastian Mika, & Gilles Blanchard. (2009). How Wrong Can We Get? A Review of Machine Learning Approaches and Error Bars. Combinatorial Chemistry & High Throughput Screening. 12(5). 453–468. 23 indexed citations

9.

Quiñonero-Candela, Joaquin, Masashi Sugiyama, Anton Schwaighofer, & Neil D. Lawrence. (2009). When Training and Test Sets Are Different: Characterizing Learning Transfer. 3–28. 5 indexed citations

10.

Quiñonero-Candela, Joaquin, Masashi Sugiyama, Anton Schwaighofer, & Neil D. Lawrence. (2009). Introduction to Dataset Shift. 1–1. 1 indexed citations

11.

Schroeter, Timon, Anton Schwaighofer, Sebastian Mika, et al.. (2007). Predicting Lipophilicity of Drug‐Discovery Molecules using Gaussian Process Models. ChemMedChem. 2(9). 1265–1267. 22 indexed citations

12.

Schroeter, Timon, Anton Schwaighofer, Sebastian Mika, et al.. (2007). Estimating the domain of applicability for machine learning QSAR models: a study on aqueous solubility of drug discovery molecules. Journal of Computer-Aided Molecular Design. 21(12). 651–664. 35 indexed citations

13.

Schroeter, Timon, Anton Schwaighofer, Sebastian Mika, et al.. (2007). Machine Learning Models for Lipophilicity and Their Domain of Applicability. Molecular Pharmaceutics. 4(4). 524–538. 23 indexed citations

14.

Schroeter, Timon, Anton Schwaighofer, Sebastian Mika, et al.. (2007). Estimating the domain of applicability for machine learning QSAR models: a study on aqueous solubility of drug discovery molecules. Journal of Computer-Aided Molecular Design. 21(9). 485–498. 51 indexed citations

15.

Schwaighofer, Anton, Volker Tresp, & Kai Yu. (2004). Learning Gaussian Process Kernels via Hierarchical Bayes. Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft). 17. 1209–1216. 112 indexed citations

16.

Yu, Kai, Anton Schwaighofer, Volker Tresp, Xiaowei Xu, & H.-P. Kriegel. (2004). Probabilistic memory-based collaborative filtering. IEEE Transactions on Knowledge and Data Engineering. 16(1). 56–69. 207 indexed citations

17.

Schwaighofer, Anton, et al.. (2003). GPPS: A Gaussian Process Positioning System for Cellular Networks. Neural Information Processing Systems. 16. 579–586. 101 indexed citations

18.

Schwaighofer, Anton, et al.. (2002). The RA Scanner: Prediction of Rheumatoid Joint Inflammation Based on Laser Imaging. Neural Information Processing Systems. 15. 1433–1440. 5 indexed citations

19.

Schwaighofer, Anton & Volker Tresp. (2002). Transductive and Inductive Methods for Approximate Gaussian Process Regression. Neural Information Processing Systems. 15. 977–984. 42 indexed citations

20.

Williams, Christopher K. I., Carl Edward Rasmussen, Anton Schwaighofer, & Volker Tresp. (2002). Observations on the Nyström Method for Gaussian Processes. 4 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