| 2018 | PAKDD | Classification with Reject Option Using Conformal Prediction. | Henrik Linusson, Ulf Johansson, Henrik Bostrm, Tuve Lfstrm |
| 2017 | IJCNN | Model-agnostic nonconformity functions for conformal classification. | Ulf Johansson, Henrik Linusson, Tuve Lfstrm, Henrik Bostrm |
| 2016 | PAKDD | Reliable Confidence Predictions Using Conformal Prediction. | Henrik Linusson, Ulf Johansson, Henrik Bostrm, Tuve Lfstrm |
| 2014 | PAKDD | Signed-Error Conformal Regression. | Henrik Linusson, Ulf Johansson, Tuve Lfstrm |
| 2013 | CEC | Evolved decision trees as conformal predictors. | Ulf Johansson, Rikard Knig, Tuve Lfstrm, Henrik Bostrm |
| 2013 | ICDM | Conformal Prediction Using Decision Trees. | Ulf Johansson, Henrik Bostrm, Tuve Lfstrm |
| 2013 | IJCNN | Random brains. | Ulf Johansson, Tuve Lfstrm, Henrik Bostrm |
| 2013 | IJCNN | Effective utilization of data in inductive conformal prediction using ensembles of neural networks. | Tuve Lfstrm, Ulf Johansson, Henrik Bostrm |
| 2012 | IJCNN | Producing implicit diversity in ANN ensembles. | Ulf Johansson, Tuve Lfstrm |
| 2011 | CEC | One tree to explain them all. | Ulf Johansson, Cecilia Snstrd, Tuve Lfstrm |
| 2011 | SMC | Locally induced predictive models. | Ulf Johansson, Tuve Lfstrm, Cecilia Snstrd |
| 2010 | CEC | Improving GP classification performance by injection of decision trees. | Rikard Knig, Ulf Johansson, Tuve Lfstrm, Lars Niklasson |
| 2010 | EUROGP | Using Imaginary Ensembles to Select GP Classifiers. | Ulf Johansson, Rikard Knig, Tuve Lfstrm, Lars Niklasson |
| 2010 | IJCNN | Comparing methods for generating diverse ensembles of artificial neural networks. | Tuve Lfstrm, Ulf Johansson, Henrik Bostrm |
| 2010 | IDA | Oracle Coached Decision Trees and Lists. | Ulf Johansson, Cecilia Snstrd, Tuve Lfstrm |
| 2009 | CEC | Using genetic programming to obtain implicit diversity. | Ulf Johansson, Cecilia Snstrd, Tuve Lfstrm, Rikard Knig |
| 2009 | CIDM | Ensemble member selection using multi-objective optimization. | Tuve Lfstrm, Ulf Johansson, Henrik Bostrm |
| 2008 | CEC | Increasing rule extraction accuracy by post-processing GP trees. | Ulf Johansson, Rikard Knig, Tuve Lfstrm, Lars Niklasson |
| 2008 | ICMLA | On the Use of Accuracy and Diversity Measures for Evaluating and Selecting Ensembles of Classifiers. | Tuve Lfstrm, Ulf Johansson, Henrik Bostrm |
| 2008 | IJCNN | The problem with ranking ensembles based on training or validation performance. | Ulf Johansson, Tuve Lfstrm, Henrik Bostrm |
| 2008 | PAKDD | Evaluating Standard Techniques for Implicit Diversity. | Ulf Johansson, Tuve Lfstrm, Lars Niklasson |
| 2007 | FUSION | Empirically investigating the importance of diversity. | Tuve Lfstrm, Ulf Johansson, Lars Niklasson |
| 2007 | IJCNN | The Importance of Diversity in Neural Network Ensembles - An Empirical Investigation. | Ulf Johansson, Tuve Lfstrm, Lars Niklasson |
| 2006 | FlAIRS | Introducing GEMS - A Novel Technique for Ensemble Creation. | Ulf Johansson, Tuve Lfstrm, Rikard Knig, Lars Niklasson |
| 2006 | FUSION | Benefits of relating the Retail Domain and Information Fusion. | Tuve Lfstrm, Rikard Knig, Ulf Johansson, Lars Niklasson, Mattias Strand, Tom Ziemke |
| 2006 | ICAISC | Genetically Evolved Trees Representing Ensembles. | Ulf Johansson, Tuve Lfstrm, Rikard Knig, Lars Niklasson |
| 2006 | ICMLA | Rule Extraction from Opaque Models-- A Slightly Different Perspective. | Ulf Johansson, Tuve Lfstrm, Rikard Knig, Cecilia Snstrd, Lars Niklasson |
| 2006 | IJCNN | Building Neural Network Ensembles using Genetic Programming. | Ulf Johansson, Tuve Lfstrm, Rikard Knig, Lars Niklasson |
| 2004 | ICONIP | Rule Extraction by Seeing Through the Model. | Tuve Lfstrm, Ulf Johansson, Lars Niklasson |