Ulf Johansson

Professor Datavetenskap
Avdelningen för datavetenskap , Tekniska Högskolan
Presentation Publikationer

Ulf Johansson is a Full Professor of Computer Science at the School of Engineering, Jönköping University. He earned his PhD in Computer Science from Linköping University in 2007, after completing a Master of Science in Computer Science and Engineering at Chalmers University of Technology.

His research is situated within Artificial Intelligence (AI), with a particular focus on developing trustworthy machine learning (ML) methods that combine predictive performance with interpretability. Over the past decade, his primary research interest has been uncertainty quantification, where he has been a strong advocate and active contributor to the field of conformal prediction, a mathematically rigorous framework that enables reliable confidence measures for individual predictions.

In addition to advancing foundational research, Johansson has a strong track record of securing competitive research funding, often for projects conducted in close collaboration with industrial partners. His work typically combines methodological innovation with real-world relevance, particularly in domains such as manufacturing, retail, logistics, and health science.

He also contributes extensively to the international research community, serving as Area Chair at leading AI and data science conferences, including CIKM and KDD, and as a reviewer for top-tier journals.

Johansson is actively engaged in international academic collaboration. He works frequently with researchers at Royal Holloway, University of London, including co-organizing international research conferences in conformal prediction. He also participated in the Erasmus Mundus Joint Doctorate Programme SMDTex, involving partner universities in France, China, Italy, and Romania, where he was the main supervisor of a PhD student with co-supervisors from France and China. In addition, he has delivered several tutorials on conformal prediction and Venn predictors for PhD students at international research conferences.

As an educator, Johansson has over two decades of teaching experience across all academic levels, from undergraduate to doctoral studies. His portfolio spans a wide range of subjects in computer science and AI, including foundations of computer science (e.g., algorithms, data structures, and programming methodology), as well as databases, data science, and machine learning. He has taught programming in multiple paradigms and languages; imperative (C), object-oriented (C++ and Java), functional (Haskell and ML), and logic programming (Prolog), and in recent years has also taught Python, particularly in data science and AI-focused courses. This breadth enables him to guide students in understanding fundamental computational principles beyond any single syntax or tool.

Johansson has played a central role in educational development at Jönköping University. He designed and launched the university’s flagship Computer Science and Engineering (CSE) program in 2020, which has become one of the School of Engineering’s most successful offerings. He is currently leading the creation of a new international master’s program in Software Engineering for AI Systems (SE4AI), scheduled to launch in 2026.

Although his professorial role includes extensive research and leadership responsibilities, Johansson has consistently prioritised active involvement in teaching. He continues to teach and take responsibility for foundational courses, including those for first-year students. This long-term commitment reflects his belief that early-stage teaching is crucial for shaping students’ academic development and fostering long-term success.

Here is his Google Scholar webpage:

Google Scholar Ulf Johansson

Artikel

Szabadvary, J., Löfström, T., Johansson, U., Sönströd, C., Ahlberg, E., Carlsson, L. (2025). Classification with reject option: Distribution-free error guarantees via conformal prediction MACHINE LEARNING WITH APPLICATIONS, 20. More information
Löfström, T., Löfström, H., Johansson, U., Sönströd, C., Matela, R. (2025). Calibrated explanations for regression Machine Learning, 114(4). More information
Löfström, H., Löfström, T., Johansson, U., Sönströd, C. (2024). Calibrated explanations: With uncertainty information and counterfactuals Expert systems with applications, 246. More information
Löfström, H., Löfström, T., Johansson, U., Sönströd, C. (2023). Investigating the impact of calibration on the quality of explanations Annals of Mathematics and Artificial Intelligence. More information
Johansson, U., Löfström, T., Boström, H. (2023). Conformal Predictive Distribution Trees Annals of Mathematics and Artificial Intelligence. More information
Johansson, U., Sönströd, C., Löfström, T., Boström, H. (2022). Rule extraction with guarantees from regression models Pattern Recognition, 126. More information
Linusson, H., Johansson, U., Boström, H. (2020). Efficient conformal predictor ensembles Neurocomputing, 397, 266-278. More information
Johansson, U., Löfström, T., Linusson, H., Boström, H. (2019). Efficient Venn Predictors using Random Forests Machine Learning, 108(3), 535-550. More information
Buendia, R. Kogej, T. Engkvist, O. Carlsson, L. Linusson, H. Johansson, U. , ... Ahlberg E. (2019). Accurate Hit Estimation for Iterative Screening Using Venn-ABERS Predictors Journal of Chemical Information and Modeling, 59(3), 1230-1237. More information
Johansson, U., Linusson, H., Löfström, T., Boström, H. (2018). Interpretable regression trees using conformal prediction Expert systems with applications, 97, 394-404. More information
Löfström, H., Löfström, T., Johansson, U. (2018). Interpretable instance-based text classification for social science research projects Archives of Data Science, Series A, 5(1). More information
Boström, H., Linusson, H., Löfström, T., Johansson, U. (2017). Accelerating difficulty estimation for conformal regression forests Annals of Mathematics and Artificial Intelligence, 81(1-2), 125-144. More information
Löfström, T., Boström, H., Linusson, H., Johansson, U. (2015). Bias reduction through conditional conformal prediction Intelligent Data Analysis, 19(6), 1355-1375. More information
Johansson, U., Boström, H., Löfström, T., Linusson, H. (2014). Regression conformal prediction with random forests Machine Learning, 97(1-2), 155-176. More information
Johansson, U., Sönströd, C., Löfström, T., Boström, H. (2012). Obtaining accurate and comprehensible classifiers using oracle coaching Intelligent Data Analysis, Volume 16(Number 2), 247-263. More information

Antologibidrag

Maalej, A., Johansson, U., Löfström, T. (2025). Evaluating Calibration Techniques for Reliable Predictions. In: Letian Huang (Ed.), Machine Learning and Soft Computing: 9th International Conference, ICMLSC 2025, Tokyo, Japan, January 24–26, 2025, Revised Selected Papers, Part II (pp. 159 -175). More information
Dahlbom, A., Riveiro, M., König, R., Johansson, U., Brattberg, P. (2014). Supporting Golf Coaching with 3D Modeling of Swings. In: Sportinformatik X: Jahrestagung der dvs-Sektion Sportinformatik (pp. 142 -148). Hamburg: Feldhaus Verlag More information
Johansson, U., König, R., Löfström, T., Sönströd, C., Niklasson, L. (2009). Post-processing Evolved Decision Trees. In: Ajith Abraham (Ed.), Foundations of Computational Intelligence (pp. 149 -164). More information

Konferensbidrag

Johansson, U., Maalej, A., Sönströd, C. (2025). Explaining Set-Valued Predictions: SHAP Analysis for Conformal Classification. 14th Symposium on Conformal and Probabilistic Prediction with Applications, COPA 2025, 10 September 2025 - 12 September 2025, London. More information
Maalej, A., Sönströd, C., Johansson, U. (2025). Counterfactual Explanations for Conformal Prediction Sets. 14th Symposium on Conformal and Probabilistic Prediction with Applications, COPA 2025,10 September 2025 - 12 September 2025, London. More information
Sönströd, C., Johansson, U. (2025). Rule Extraction with Reject Option. 9th International Conference, ICMLSC, 2025, Tokyo, Japan, January 24–26, 2025. More information
Löfström, T., Löfström, H., Johansson, U. (2024). Calibrated explanations for multi-class. The 13th Symposium on Conformal and Probabilistic Prediction with Applications, 9-11 September 2024, Politecnico di Milano, Milano, Italy. More information
Alkhatib, A., Boström, H., Ennadir, S., Johansson, U. (2023). Approximating Score-based Explanation Techniques Using Conformal Regression. 12th Symposium on Conformal and Probabilistic Prediction with Applications, COPA 2023 Limassol 13 September 2023 through 15 September 2023. More information
Johansson, U., Sönströd, C., Löfström, T., Boström, H. (2023). Confidence Classifiers with Guaranteed Accuracy or Precision. Twelfth Symposium on Conformal and Probabilistic Prediction with Applications, 13-15 September 2023, Limassol, Cyprus. More information
Löfström, T., Bondaletov, A., Ryasik, A., Boström, H., Johansson, U. (2023). Tutorial on using Conformal Predictive Systems in KNIME. Twelfth Symposium on Conformal and Probabilistic Prediction with Applications, 13-15 September 2023, Limassol, Cyprus. More information
Johansson, U., Löfström, T., Sönströd, C., Löfström, H. (2023). Conformal Prediction for Accuracy Guarantees in Classification with Reject Option. International Conference on Modeling Decisions for Artificial Intelligence Umeå, Sweden 19 June 2023. More information
Sweidan, D., Johansson, U., Alenljung, B., Gidenstam, A. (2023). Improved Decision Support for Product Returns using Probabilistic Prediction. 2023 Congress in Computer Science, Computer Engineering, and Applied Computing, CSCE 2023 Las Vegas 24 July 2023 through 27 July 2023. More information
Johansson, U., Boström, H., Nguyen, K., Luo, Z., Carlsson, L. (2022). Preface. 11th Symposium on Conformal and Probabilistic Prediction with Applications, COPA 2022 Brighton 24 August 2022 through 26 August 2022. More information
Sweidan, D., Johansson, U., Gidenstam, A., Alenljung, B. (2022). Predicting Customer Churn in Retailing. Proceedings - 21st IEEE International Conference on Machine Learning and Applications, ICMLA 2022 Nassau 12 December 2022 through 14 December 2022. More information
Johansson, U., Löfström, T., Ståhl, N. (2022). Well-Calibrated Rule Extractors. 11th Symposium on Conformal and Probabilistic Prediction with Applications, 24-26 August 2022, Brighton, UK. More information
Alkhatib, A., Boström, H., Johansson, U. (2022). Assessing Explanation Quality by Venn Prediction. 11th Symposium on Conformal and Probabilistic Prediction with Applications, 24-26 August 2022, Brighton, UK. More information
Löfström, T., Ryasik, A., Johansson, U. (2022). Tutorial for using conformal prediction in KNIME. 11th Symposium on Conformal and Probabilistic Prediction with Applications, 24-26 August 2022, Brighton, UK. More information
Löfström, H., Hammar, K., Johansson, U. (2022). A meta survey of quality evaluation criteria in explanation methods. Cham: Springer, CAiSE Forum 2022, Leuven, Belgium, June 6–10, 2022. More information
Sattari, A., Johansson, U., Wilderoth, E., Jakupovic, J., Larsson-Green, P. (2022). The Interpretable Representation of Football Player Roles Based on Passing/Receiving Patterns. 8th International Workshop, MLSA 2021, Virtual Event, September 13, 2021, Revised Selected Papers. More information
Johansson, U., Löfström, T., Boström, H. (2021). Well-Calibrated and Sharp Interpretable Multi-Class Models. 18th International Conference, MDAI 2021, Umeå, Sweden, September 27–30, 2021, Proceedings. More information
Arvidsson, S., Gabrielsson, P., Johansson, U. (2021). Texture Mapping of Flags onto Polandball Characters using Convolutional Neural Nets. 2021 International Joint Conference on Neural Networks (IJCNN), 18-22 July 2021, Shenzhen, China. More information
Johansson, U., Löfström, T., Boström, H. (2021). Calibrating multi-class models. Conformal and Probabilistic Prediction and Applications, 8-10 September 2021, Virtual. More information
Boström, H., Johansson, U., Löfström, T. (2021). Mondrian conformal predictive distributions. Conformal and Probabilistic Prediction and Applications, 8-10 September 2021, Virtual. More information
Johansson, U., Bostrom, H., Löfström, T. (2021). Investigating Normalized Conformal Regressors. 2021 IEEE Symposium Series on Computational Intelligence, SSCI 2021, 5 December 2021 through 7 December 2021. More information
Sweidan, D., Johansson, U., Gidenstam, A. (2020). Predicting returns in men's fashion. Singapore: World Scientific, 15th Symposium of Intelligent Systems and Knowledge Engineering (ISKE) held jointly with 14th International FLINS Conference (FLINS), Cologne, Germany, 18-21 August, 2020. More information
Johansson, U., Löfström, T. (2020). Well-calibrated and specialized probability estimation trees. 2020 SIAM International Conference on Data Mining, SDM 2020, 7 May 2020 through 9 May 2020. More information
Giri, C., Johansson, U., Löfström, T. (2019). Predictive modeling of campaigns to quantify performance in fashion retail industry. 2019 IEEE International Conference on Big Data, Big Data 2019, Los Angeles, United States, 9-12 December 2019. More information
Johansson, U., Sonstrod, C., Löfström, T., Bostrom, H. (2019). Customized interpretable conformal regressors. 6th IEEE International Conference on Data Science and Advanced Analytics, DSAA 2019, Washington, United States, 5 - 8 October, 2019. More information
Johansson, U., Löfström, T., Boström, H., Sönströd, C. (2019). Interpretable and Specialized Conformal Predictors. Proceedings of the Eighth Symposium on Conformal and Probabilistic Prediction and Applications, 9-11 September 2019, Golden Sands, Bulgaria. More information
Boström, H., Johansson, U., Vesterberg, A. (2019). Predicting with Confidence from Survival Data. Proceedings of the Eighth Symposium on Conformal and Probabilistic Prediction and Applications, 9-11 September 2019, Golden Sands, Bulgaria. More information
Johansson, U., Gabrielsson, P. (2019). Are Traditional Neural Networks Well-Calibrated?. 2019 International Joint Conference on Neural Networks, IJCNN 2019, Budapest, Hungary, 14 - 19 July 2019. More information
Johansson, U., Löfström, T., Boström, H. (2019). Calibrating probability estimation trees using Venn-Abers predictors. 19th SIAM International Conference on Data Mining, SDM 2019, Hyatt Regency Calgary, Calgary, Canada, 2 - 4 May 2019. More information
Linusson, H., Johansson, U., Boström, H., Löfström, T. (2018). Classification with reject option using conformal prediction. 22nd Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2018; Melbourne; Australia; 3 June 2018 through 6 June 2018. More information
Johansson, U., Löfström, T., Sundell, H. (2018). Venn predictors using lazy learners. The 2018 World Congress in Computer Science, Computer Engineering & Applied Computing, July 30 - August 02, Las Vegas, Nevada, USA. More information
Johansson, U., Löfström, T., Sundell, H., Linusson, H., Gidenstam, A., Boström, H. (2018). Venn predictors for well-calibrated probability estimation trees. Proceedings of the Seventh Workshop on Conformal and Probabilistic Prediction and Applications, 11-13 June 2018. More information
Sundell, H., Löfström, T., Johansson, U. (2018). Explorative multi-objective optimization of marketing campaigns for the fashion retail industry. 13th International Conference on Fuzzy Logic and Intelligent Technologies in Nuclear Science (FLINS), Belfast, Ireland, 21-24 August, 2018. More information
Löfström, T., Johansson, U., Balkow, J., Sundell, H. (2018). A data-driven approach to online fitting services. 13th International Conference on Fuzzy Logic and Intelligent Technologies in Nuclear Science (FLINS), Belfast, Ireland, 21-24 August, 2018. More information
Ahlberg, E. Winiwarter, S. Boström, H. Linusson, H. Löfström, T. Norinder, U. , ... Carlsson L. (2017). Using conformal prediction to prioritize compound synthesis in drug discovery. The 6th Symposium on Conformal and Probabilistic Prediction with Applications, (COPA 2017), 13-16 June, 2017, Stockholm, Sweden. More information
König, R., Johansson, U., Riveiro, M., Brattberg, P. (2017). Modeling golf player skill using machine learning. 1st IFIP TC 5, WG 8.4, 8.9, 12.9 International Cross-Domain Conference on Machine Learning and Knowledge Extraction, CD-MAKE 2017; Reggio; Italy; 29 August 2017 through 1 September 2017. More information
Johansson, U., Linusson, H., Löfström, T., Boström, H. (2017). Model-agnostic nonconformity functions for conformal classification. 2017 International Joint Conference on Neural Networks, IJCNN 2017, 14 May 2017 through 19 May 2017. More information
Linusson, H., Norinder, U., Boström, H., Johansson, U., Löfström, T. (2017). On the calibration of aggregated conformal predictors. The 6th Symposium on Conformal and Probabilistic Prediction with Applications, (COPA 2017), 13-16 June, 2017, Stockholm, Sweden. More information
Linusson, H., Johansson, U., Boström, H., Löfström, T. (2016). Reliable Confidence Predictions Using Conformal Prediction. PAKDD 2016: Advances in Knowledge Discovery and Data Mining, Auckland, April 19-22, 2016. More information
Boström, H., Linusson, H., Löfström, T., Johansson, U. (2016). Evaluation of a variance-based nonconformity measure for regression forests. 5th International Symposium on Conformal and Probabilistic Prediction with Applications, COPA 2016; Madrid; Spain; 20 April 2016 through 22 April 2016. More information
Johansson, U., Konig, R., Brattberg, P., Dahlbom, A., Riveiro, M. (2016). Mining trackman golf data. International Conference on Computational Science and Computational Intelligence, CSCI 2015, 7 December 2015 through 9 December 2015. More information
Gabrielsson, P., Johansson, U. (2015). High-frequency equity index futures trading using recurrent reinforcement learning with candlesticks. IEEE Symposium Series on Computational Intelligence, SSCI 2015, 8 December 2015 through 10 December 2015. More information
Carlsson, L., Ahlberg, E., Boström, H., Johansson, U., Linusson, H. (2015). Modifications to p-Values of conformal predictors. 3rd International Symposium on Statistical Learning and Data Sciences, SLDS 2015; Egham; United Kingdom; 20 April 2015 through 23 April 2015. More information
Riveiro, M., Dahlbom, A., König, R., Johansson, U., Brattberg, P. (2015). Supporting Golf Coaching and Swing Instruction with Computer-Based Training Systems. Learning and Collaboration Technologies. More information
Sundell, H., König, R., Johansson, U. (2015). Pragmatic Approach to Association Rule Learning in Real-World Scenarios. The 2015 International Conference on Computational Science and Computational Intelligence (CSCI'15). More information
Johansson, U., Ahlberg, E., Boström, H., Carlsson, L., Linusson, H., Sönströd, C. (2015). Handling small calibration sets in mondrian inductive conformal regressors. 3rd International Symposium on Statistical Learning and Data Sciences, SLDS 2015; Egham; United Kingdom; 20 April 2015 through 23 April 2015. More information
Johansson, U., Sönströd, C., Linusson, H. (2015). Efficient conformal regressors using bagged neural nets. International Joint Conference on Neural Networks, IJCNN 2015, 12 July 2015 through 17 July 2015. More information
König, R., Johansson, U., Lindqvist, A., Brattberg, P. (2015). Interesting regression- and model trees through variable restrictions. 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, IC3K 2015, 12 November 2015 through 14 November 2015. More information
Johansson, U., Sönströd, C., Linusson, H., Boström, H. (2014). Regression Trees for Streaming Data with Local Performance Guarantees. IEEE International Conference on Big Data, 27-30 October, 2014, Washington, DC, USA. More information
Linusson, H., Johansson, U., Boström, H., Löfström, T. (2014). Efficiency Comparison of Unstable Transductive and Inductive Conformal Classifiers. Artificial Intelligence Applications and Innovations. More information
Johansson, U., König, R., Linusson, H., Löfström, T., Boström, H. (2014). Rule Extraction with Guaranteed Fidelity. Artificial Intelligence Applications and Innovations. More information
König, R., Johansson, U. (2014). Rule Extraction using Genetic Programming for Accurate Sales Forecasting. 5th IEEE Symposium on Computational Intelligence and Data Mining (CIDM 2014), 9-12 december, Orlando, FL, USA. More information
Linusson, H., Johansson, U., Löfström, T. (2014). Signed-Error Conformal Regression. 18th Pacific-Asia Conference, PAKDD 2014 Tainan, Taiwan, May 13-16, 2014. More information
Gabrielsson, P., Johansson, U., König, R. (2014). Co-Evolving Online High-Frequency Trading Strategies Using Grammatical Evolution. IEEE Conference on Computational Intelligence for Financial Engineering & Economics, 27-28 March, 2014, London, UK. More information
Johansson, U., Sönströd, C., König, R. (2014). Accurate and Interpretable Regression Trees using Oracle Coaching. 5th IEEE Symposium Computational Intelligence and Data Mining, 9-12 Decmber, Orlando, FL, USA. More information
Johansson, U., Boström, H., Löfström, T. (2013). Conformal Prediction Using Decision Trees. IEEE International Conference on Data Mining. More information
Löfström, T., Johansson, U., Boström, H. (2013). Effective Utilization of Data in Inductive Conformal Prediction using Ensembles of Neural Networks. International Joint Conference on Neural Networks, Dallas, TX, USA, August 4-9, 2013.. More information
Johansson, U., König, R., Löfström, T., Boström, H. (2013). Evolved Decision Trees as Conformal Predictors. IEEE Congress on Evolutionary Computation, 20-23 June 2013. More information
Johansson, U., Löfström, T., Boström, H. (2013). Overproduce-and-Select: The Grim Reality. IEEE Symposium on Computational Intelligence and Ensemble Learning (CIEL), 16-19 April 2013 , Singapore. More information
Johansson, U., Löfström, T., Boström, H. (2013). Random Brains. International Joint Conference on Neural Networks, Dallas, TX, USA, August 4-9, 2013.. More information
Gabrielsson, P., König, R., Johansson, U. (2013). Evolving Hierarchical Temporal Memory-Based Trading Models. Applications of Evolutionary Computation. More information
Johansson, U., Löfström, T. (2012). Producing Implicit Diversity in ANN Ensembles. Neural Networks (IJCNN), The 2012 International Joint Conference on. More information
Gabrielsson, P., König, R., Johansson, U. (2012). Hierarchical Temporal Memory-based algorithmic trading of financial markets. Computational Intelligence for Financial Engineering & Economics (CIFEr), New York, NY, 2012. More information
Johansson, U., Sönströd, C., Löfström, T. (2011). One Tree to Explain Them All. IEEE Congress on Evolutionary Computation (CEC). More information
Johansson, U., Löfström, T., Sönströd, C. (2011). Locally Induced Predictive Models. IEEE International Conference on Systems, Man, and Cybernetics. More information
Johansson, U., König, R., Löfström, T., Niklasson, L. (2010). Using Imaginary Ensembles to Select GP Classifiers. 13th European Conference, EuroGP 2010, Istanbul, Turkey, April 7-9, 2010. More information
Johansson, U., Sönströd, C., Norinder, U., Boström, H., Löfström, T. (2010). Using Feature Selection with Bagging and Rule Extraction in Drug Discovery. Advances in Intelligent Decision Technologies, Second KES International Symposium IDT 2010. More information
König, R., Johansson, U., Löfström, T., Niklasson, L. (2010). Improving GP Classification Performance by Injection of Decision Trees. WCCI 2010 IEEE World Congress on Computational Intelligence, CEC 2010. More information
Johansson, U., Sönströd, C., Löfström, T. (2010). Oracle Coached Decision Trees and Lists. Advances in Intelligent Data Analysis IX, 9th International Symposium, IDA 2010. More information
Löfström, T., Johansson, U., Boström, H. (2010). Comparing Methods for Generating Diverse Ensembles of Artificial Neural Networks. WCCI 2010 IEEE World Congress on Computational Intelligence, IJCNN 2010. More information
Johansson, U., Sönströd, C., Löfström, T., König, R. (2009). Using Genetic Programming to Obtain Implicit Diversity. 2009 IEEE Congress on Evolutionary Computation (CEC 2009), Trondheim, Norge. More information
Löfström, T., Johansson, U., Borström, H. (2009). Ensemble Member Selection Using Multi-Objective Optimization. 2009 IEEE SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE AND DATA MINING, Nashville, TN, USA. More information
Löfström, T., Johansson, U., Boström, H. (2009). Using Optimized Optimization Criteria in Ensemble Member Selection. SWIFT 2008 - Skövde Workshop on Information Fusion Topics. More information
Sönströd, C., Johansson, U., Löfström, T. (2009). Evaluating Algorithms for Concept Description. 5th International Conference on Data Mining - DMIN 09, Las Vegas, USA. More information
Löfström, T., Johansson, U., Boström, H. (2008). The Problem with Ranking Ensembles Based on Training or Validation Performance. IJCNN 2008, Hong Kong, June 1- 6, 2008. More information
Johansson, U., König, R., Löfström, T., Niklasson, L. (2008). Increasing Rule Extraction Accuracy by Post-processing GP Trees. CEC 2008, Hong Kong, June 1-6, 2008. More information
Johansson, U., Sönströd, C., Boström, H., Löfström, T. (2008). Chipper: A Novel Algorithm for Concept Description. Paper presented at the 10th Scandinavian Conference on Artificial Intelligence SCAI 2008. More information
Johansson, U., Löfström, T., Niklasson, L. (2008). Evaluating Standard Techniques for Implicit Diversity. Pacific-Asia Conference on Knowledge Discovery and Data Mining. More information
Löfström, T., Johansson, U., Boström, H. (2008). On the Use of Accuracy and Diversity Measures for Evaluating and Selecting Ensembles of Classifiers. Seventh International Conference on Machine Learning and Applications. More information
Johansson, U., Löfström, T., Niklasson, L. (2007). The Importance of Diversity in Neural Network Ensembles: An Empirical Investigation. The International Joint Conference on Neural Networks. More information
Johansson, U., Löfström, T., Niklasson, L. (2007). Empirically Investigating the Importance of Diversity. International Conference on Information Fusion. More information

Rapport

Löfström, T., Ralsmark, H., Johansson, U. (2021). Collusion in algorithmic pricing. Stockholm: Konkurrensverket More information
Johansson, U., Sundström, M., Sundell, H., Rickard, K., Jenny, B. (2016). Dataanalys för ökad kundförståelse. Stockholm: Handelsrådet More information
Löfström, T., Linnusson, H., Sönströd, C., Johansson, U. (2015). System Health Monitoring using Conformal Anomaly Detection. Borås: Högskolan i Borås More information