Tuve Löfström

801 total citations
56 papers, 467 citations indexed

About

Tuve Löfström is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, Tuve Löfström has authored 56 papers receiving a total of 467 indexed citations (citations by other indexed papers that have themselves been cited), including 46 papers in Artificial Intelligence, 8 papers in Information Systems and 8 papers in Computer Vision and Pattern Recognition. Recurrent topics in Tuve Löfström's work include Machine Learning and Data Classification (27 papers), Neural Networks and Applications (21 papers) and Imbalanced Data Classification Techniques (10 papers). Tuve Löfström is often cited by papers focused on Machine Learning and Data Classification (27 papers), Neural Networks and Applications (21 papers) and Imbalanced Data Classification Techniques (10 papers). Tuve Löfström collaborates with scholars based in Sweden, United Kingdom and Germany. Tuve Löfström's co-authors include Ulf Johansson, Henrik Boström, Henrik Linusson, Lars Niklasson, Rikard König, Rachid Oucheikh, Ulf Norinder, Ernst Ahlberg, Lars Carlsson and R. König and has published in prestigious journals such as SHILAP Revista de lepidopterología, Expert Systems with Applications and Pattern Recognition.

In The Last Decade

Tuve Löfström

50 papers receiving 424 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Tuve Löfström Sweden 12 284 51 49 48 42 56 467
Jesús Soto Mexico 7 301 1.1× 53 1.0× 79 1.6× 42 0.9× 17 0.4× 17 508
Francisco Herrera Triguero Spain 10 200 0.7× 45 0.9× 38 0.8× 25 0.5× 13 0.3× 26 380
Hong Mo China 12 198 0.7× 41 0.8× 109 2.2× 29 0.6× 37 0.9× 44 413
Alireza Farhangfar Canada 6 276 1.0× 42 0.8× 21 0.4× 75 1.6× 75 1.8× 8 478
Frumen Olivas Mexico 8 398 1.4× 78 1.5× 145 3.0× 51 1.1× 58 1.4× 13 559
Zhao Xu China 11 176 0.6× 13 0.3× 35 0.7× 30 0.6× 11 0.3× 40 327
Salih Berkan Aydemı̇r Türkiye 10 189 0.7× 99 1.9× 93 1.9× 40 0.8× 41 1.0× 19 451
Guilherme O. Campos Brazil 3 387 1.4× 21 0.4× 57 1.2× 32 0.7× 48 1.1× 5 445
Piotr Duda Poland 12 453 1.6× 18 0.4× 64 1.3× 52 1.1× 14 0.3× 24 637
Gracia Sánchez Spain 11 282 1.0× 130 2.5× 39 0.8× 37 0.8× 13 0.3× 28 468

Countries citing papers authored by Tuve Löfström

Since Specialization
Citations

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

Fields of papers citing papers by Tuve Löfström

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tuve Löfström

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

All Works

20 of 20 papers shown
1.
Löfström, Tuve, et al.. (2025). Beyond conformal predictors: Adaptive Conformal Inference with confidence predictors. Pattern Recognition. 170. 111999–111999. 2 indexed citations
2.
Löfström, Tuve, et al.. (2025). Classification with reject option: Distribution-free error guarantees via conformal prediction. Machine Learning with Applications. 20. 100664–100664.
3.
Löfström, Tuve, et al.. (2025). Calibrated explanations for regression. Machine Learning. 114(4). 2 indexed citations
4.
Riveiro, Maria, et al.. (2024). Multimodal fine-grained grocery product recognition using image and OCR text. Machine Vision and Applications. 35(4). 2 indexed citations
5.
Löfström, Tuve, et al.. (2023). Investigating the impact of calibration on the quality of explanations. Annals of Mathematics and Artificial Intelligence. 2 indexed citations
6.
Johansson, Ulf, et al.. (2022). Rule extraction with guarantees from regression models. Pattern Recognition. 126. 108554–108554. 11 indexed citations
7.
Oucheikh, Rachid, Tuve Löfström, Ernst Ahlberg, & Lars Carlsson. (2021). Rolling Cargo Management Using a Deep Reinforcement Learning Approach. SHILAP Revista de lepidopterología. 5(1). 10–10. 12 indexed citations
8.
Löfström, Tuve, et al.. (2018). Interpretable Instance-Based Text Classification for Social Science Research Projects. Repository KITopen (Karlsruhe Institute of Technology). 2 indexed citations
9.
Löfström, Tuve. (2015). On Effectively Creating Ensembles of Classifiers : Studies on Creation Strategies, Diversity and Predicting with Confidence. KTH Publication Database DiVA (KTH Royal Institute of Technology). 5 indexed citations
10.
Johansson, Ulf, Rikard König, Tuve Löfström, & Henrik Boström. (2013). Evolved decision trees as conformal predictors. KTH Publication Database DiVA (KTH Royal Institute of Technology). 1794–1801. 8 indexed citations
11.
Johansson, Ulf, Tuve Löfström, & Henrik Boström. (2013). Random brains. 7. 1–8.
12.
Johansson, Ulf, et al.. (2009). Using genetic programming to obtain implicit diversity. 2. 2454–2459. 2 indexed citations
13.
Löfström, Tuve, Ulf Johansson, & Henrik Boström. (2008). On the Use of Accuracy and Diversity Measures for Evaluating and Selecting Ensembles of Classifiers. KTH Publication Database DiVA (KTH Royal Institute of Technology). 127–132. 11 indexed citations
14.
Johansson, Ulf, Tuve Löfström, & Henrik Boström. (2008). The problem with ranking ensembles based on training or validation performance. KTH Publication Database DiVA (KTH Royal Institute of Technology). 18. 3222–3228. 4 indexed citations
15.
Löfström, Tuve, Ulf Johansson, & Lars Niklasson. (2007). Empirically investigating the importance of diversity. 2. 1–8. 1 indexed citations
16.
Johansson, Ulf, et al.. (2006). Rule Extraction from Opaque Models-- A Slightly Different Perspective. 22–27. 7 indexed citations
17.
Johansson, Ulf, Tuve Löfström, Rikard König, & Lars Niklasson. (2006). Introducing GEMS * a Novel Technique for Ensemble Creation. The Florida AI Research Society. 700–705. 3 indexed citations
18.
Johansson, Ulf, Tuve Löfström, Rikard König, & Lars Niklasson. (2006). Why Not Use an Oracle When You Got One. International Conference on Neural Information Processing. 10. 227–236. 10 indexed citations
19.
Johansson, Ulf, Tuve Löfström, Rikard König, & Lars Niklasson. (2006). Building Neural Network Ensembles using Genetic Programming. The 2006 IEEE International Joint Conference on Neural Network Proceedings. 2. 1260–1265. 8 indexed citations
20.
Löfström, Tuve & Ulf Johansson. (2005). Predicting the Benefit of Rule Extraction: A Novel Component in Data Mining. 7(3). 3 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.

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