Generalizing the Order of Goals as an Approach to Generalizing Number. - Henrik Boström (ML, 1990)

Optimizing Horn Clause Logic Programs for Particular Modes of Use: An Analysis of Explanation-Based Learning and Partial Evaluation. - Carl Gustaf Jansson; Henrik Boström; Peter Idestam-Almquist (SCAI, 1991)

Improving Example-Guided Unfolding. - Henrik Boström (ECML, 1993)

JIGSAW: Puzzling together RUTH and SPECTRE (Extended Abstract). - Hilde Adé; Henrik Boström (ECML, 1995)

Specialization of Recursive Predicates. - Henrik Boström (ECML, 1995)

Covering vs. Divide-and-Conquer for Top-Down Induction of Logic Programs. - Henrik Boström (IJCAI, 1995)

Integrating Algorithmic Debugging and Unfolding Transformation in an Interactive Learner. - Zoltán Alexin; Tibor Gyimóthy; Henrik Boström (ECAI, 1996)

Theory-Guideed Induction of Logic Programs by Inference of Regular Languages. - Henrik Boström (ICML, 1996)

IMPUT: An Interactive Learning Tool Based on Program Specialization. - Zoltán Alexin; Tibor Gyimóthy; Henrik Boström (Intell. Data Anal., 1997)

Predicate Invention and Learning from Positive Examples Only. - Henrik Boström (ECML, 1998)

Combining Divide-and-Conquer and Separate-and-Conquer for Efficient and Effective Rule Induction. - Henrik Boström; Lars Asker (ILP, 1999)

Induction of Recursive Transfer Rules. - Henrik Boström (Learning Language in Logic, 1999)

Induction of Logic Programs by Example-Guided Unfolding. - Henrik Boström; Peter Idestam-Almquist (J. Log. Program., 1999)

Learning First Order Logic Time Series Classifiers. - Juan José Rodríguez; Carlos J. Alonso; Henrik Boström (ILP Work-in-progress reports, 2000)

Learning First Order Logic Time Series Classifiers: Rules and Boosting. - Juan J. Rodríguez Diez; Carlos Alonso González; Henrik Boström (PKDD, 2000)

Automatic Keyword Extraction Using Domain Knowledge. - Anette Hulth; Jussi Karlgren; Anna Jonsson; Henrik Boström; Lars Asker (CICLing, 2001)

Classifying Uncovered Examples by Rule Stretching. - Martin Eineborg; Henrik Boström (ILP, 2001)

Learning to recognize brain specific proteins based on low-level features from on-line prediction servers. - Mikael Huss; Henrik Boström; Lars Asker; Joakim Cöster (BIOKDD, 2001)

Boosting interval based literals. - Juan J. Rodríguez Diez; Carlos Alonso González; Henrik Boström (Intell. Data Anal., 2001)

Classification with Intersecting Rules. - Tony Lindgren; Henrik Boström (ALT, 2002)

Rule Induction for Classification of Gene Expression Array Data. - Per Lidén; Lars Asker; Henrik Boström (PKDD, 2002)

Resolving rule conflicts with double induction. - Tony Lindgren; Henrik Boström (Intell. Data Anal., 2004)

Learning to classify structured data by graph propositionalization. - Thashmee Karunaratne; Henrik Boström (Computational Intelligence, 2006)

Reducing High-Dimensional Data by Principal Component Analysis vs. Random Projection for Nearest Neighbor Classification. - Sampath Deegalla; Henrik Boström (ICMLA, 2006)

Feature vs. classifier fusion for predictive data mining a case study in pesticide classification. - Henrik Boström (FUSION, 2007)

Estimating class probabilities in random forests. - Henrik Boström (ICMLA, 2007)

Classification of Microarrays with kNN: Comparison of Dimensionality Reduction Methods. - Sampath Deegalla; Henrik Boström (IDEAL, 2007)

Using Background Knowledge for Graph Based Learning: A Case Study in Chemoinformatics. - Thashmee Karunaratne; Henrik Boström (IMECS, 2007)

Maximizing the Area under the ROC Curve with Decision Lists and Rule Sets. - Henrik Boström (SDM, 2007)

Extending Nearest Neighbor Classification with Spheres of Confidence. - Ulf Johansson; Henrik Boström; Rikard König (FLAIRS, 2008)

On evidential combination rules for ensemble classifiers. - Henrik Boström; Ronnie Johansson; Alexander Karlsson (FUSION, 2008)

Calibrating Random Forests. - Henrik Boström (ICMLA, 2008)

On the Use of Accuracy and Diversity Measures for Evaluating and Selecting Ensembles of Classifiers. - Tuve Löfström; Ulf Johansson; Henrik Boström (ICMLA, 2008)

Comprehensible Models for Predicting Molecular Interaction with Heart-Regulating Genes. - Cecilia Sönströd; Ulf Johansson; Ulf Norinder; Henrik Boström (ICMLA, 2008)

The problem with ranking ensembles based on training or validation performance. - Ulf Johansson; Tuve Löfström; Henrik Boström (IJCNN, 2008)

A study on class-specifically discounted belief for ensemble classifiers. - Ronnie Johansson; Henrik Boström; Alexander Karlsson (MFI, 2008)

Chipper - A Novel Algorithm for Concept Description. - Ulf Johansson; Cecilia Sönströd; Tuve Löfström; Henrik Boström (SCAI, 2008)

Ensemble member selection using multi-objective optimization. - Tuve Löfström; Ulf Johansson; Henrik Boström (CIDM, 2009)

Fusion of dimensionality reduction methods: A case study in microarray classification. - Sampath Deegalla; Henrik Boström (FUSION, 2009)

Improving Fusion of Dimensionality Reduction Methods for Nearest Neighbor Classification. - Sampath Deegalla; Henrik Boström (ICMLA, 2009)

Graph Propositionalization for Random Forests. - Thashmee Karunaratne; Henrik Boström (ICMLA, 2009)

Using uncertain chemical and thermal data to predict product quality in a casting process. - Catarina Dudas; Henrik Boström (KDD Workshop on Knowledge Discovery from Uncertain Data, 2009)

Pre-Processing Structured Data for Standard Machine Learning Algorithms by Supervised Graph Propositionalization - A Case Study with Medicinal Chemistry Datasets. - Thashmee Karunaratne; Henrik Boström; Ulf Norinder (ICMLA, 2010)

Comparing methods for generating diverse ensembles of artificial neural networks. - Tuve Löfström; Ulf Johansson; Henrik Boström (IJCNN, 2010)

Pin-pointing concept descriptions. - Cecilia Sönströd; Ulf Johansson; Henrik Boström; Ulf Norinder (SMC, 2010)

Concurrent Learning of Large-Scale Random Forests. - Henrik Boström (SCAI, 2011)

Choice of dimensionality reduction methods for feature and classifier fusion with nearest neighbor classifiers. - Sampath Deegalla; Henrik Boström; Keerthi Walgama (FUSION, 2012)

Can Frequent Itemset Mining Be Efficiently and Effectively Used for Learning from Graph Data? - Thashmee Karunaratne; Henrik Boström (ICMLA (1), 2012)

Extracting Patterns from Socioeconomic Databases to Characterize Small Farmers with High and Low Corn Yields in Mozambique: a Data Mining Approach. - Constantino Sotomane; Jordi Gallego-Ayala; Lars Asker; Henrik Boström; Venâncio Massingue (ICDM (Workshops), 2012)

Obtaining accurate and comprehensible classifiers using oracle coaching. - Ulf Johansson; Cecilia Sönströd; Tuve Löfström; Henrik Boström (Intell. Data Anal., 2012)

Forests of Probability Estimation Trees. - Henrik Boström (Int. J. Pattern Recognit. Artif. Intell., 2012)

Introducing Uncertainty in Predictive Modeling - Friend or Foe? - Ulf Norinder; Henrik Boström (J. Chem. Inf. Model., 2012)

Generalization of Malaria Incidence Prediction Models by Correcting Sample Selection Bias. - Orlando P. Zacarias; Henrik Boström (ADMA (2), 2013)

Predicting Adverse Drug Events by Analyzing Electronic Patient Records. - Isak Karlsson; Jing Zhao 017; Lars Asker; Henrik Boström (AIME, 2013)

Evolved decision trees as conformal predictors. - Ulf Johansson; Rikard König; Tuve Löfström; Henrik Boström (IEEE Congress on Evolutionary Computation, 2013)

Overproduce-and-select: The grim reality. - Ulf Johansson; Tuve Löfström; Henrik Boström (CIEL, 2013)

Conformal Prediction Using Decision Trees. - Ulf Johansson; Henrik Boström; Tuve Löfström (ICDM, 2013)

Random brains. - Ulf Johansson; Tuve Löfström; Henrik Boström (IJCNN, 2013)

Effective utilization of data in inductive conformal prediction using ensembles of neural networks. - Tuve Löfström; Ulf Johansson; Henrik Boström (IJCNN, 2013)

Interleaving Innovization with Evolutionary Multi-Objective Optimization in Production System Simulation for Faster Convergence. - Amos H. C. Ng; Catarina Dudas; Henrik Boström; Kalyanmoy Deb (LION, 2013)

Comparative analysis of the use of chemoinformatics-based and substructure-based descriptors for quantitative structure-activity relationship (QSAR) modeling. - Thashmee Karunaratne; Henrik Boström; Ulf Norinder (Intell. Data Anal., 2013)

Detecting adverse drug events with multiple representations of clinical measurements. - Jing Zhao 017; Aron Henriksson; Lars Asker; Henrik Boström (BIBM, 2014)

Regression trees for streaming data with local performance guarantees. - Ulf Johansson; Cecilia Sönströd; Henrik Linusson; Henrik Boström (IEEE BigData, 2014)

Handling Sparsity with Random Forests When Predicting Adverse Drug Events from Electronic Health Records. - Isak Karlsson; Henrik Boström (ICHI, 2014)

Detecting Adverse Drug Events Using Concept Hierarchies of Clinical Codes. - Jing Zhao 017; Aron Henriksson; Henrik Boström (ICHI, 2014)

Rule Extraction with Guaranteed Fidelity. - Ulf Johansson; Rikard König; Henrik Linusson; Tuve Löfström; Henrik Boström (AIAI (Workshops), 2014)

Efficiency Comparison of Unstable Transductive and Inductive Conformal Classifiers. - Henrik Linusson; Ulf Johansson; Henrik Boström; Tuve Löfström (AIAI (Workshops), 2014)

gpuRF and gpuERT: Efficient and Scalable GPU Algorithms for Decision Tree Ensembles. - Karl Jansson; Håkan Sundell; Henrik Boström (IPDPS Workshops, 2014)

Mining candidates for adverse drug interactions in electronic patient records. - Lars Asker; Henrik Boström; Isak Karlsson; Panagiotis Papapetrou; Jing Zhao 017 (PETRA, 2014)

A peek into the black box: exploring classifiers by randomization. - Andreas Henelius; Kai Puolamäki; Henrik Boström; Lars Asker; Panagiotis Papapetrou (Data Min. Knowl. Discov., 2014)

Integration of data mining and multi-objective optimisation for decision support in production systems development. - Catarina Dudas; Amos H. C. Ng; Leif Pehrsson; Henrik Boström (Int. J. Comput. Integr. Manuf., 2014)

Regression conformal prediction with random forests. - Ulf Johansson; Henrik Boström; Tuve Löfström; Henrik Linusson (Mach. Learn., 2014)

Handling Temporality of Clinical Events for Drug Safety Surveillance. - Jing Zhao 017; Aron Henriksson; Maria Kvist; Lars Asker; Henrik Boström (AMIA, 2015)

Modeling electronic health records in ensembles of semantic spaces for adverse drug event detection. - Aron Henriksson; Jing Zhao 017; Henrik Boström; Hercules Dalianis (BIBM, 2015)

Modeling heterogeneous clinical sequence data in semantic space for adverse drug event detection. - Aron Henriksson; Jing Zhao 017; Henrik Boström; Hercules Dalianis (DSAA, 2015)

Cascading adverse drug event detection in electronic health records. - Jing Zhao 017; Aron Henriksson; Henrik Boström (DSAA, 2015)

Modifications to p-Values of Conformal Predictors. - Lars Carlsson; Ernst Ahlberg; Henrik Boström; Ulf Johansson; Henrik Linusson (SLDS, 2015)

GoldenEye++: A Closer Look into the Black Box. - Andreas Henelius; Kai Puolamäki; Isak Karlsson; Jing Zhao 017; Lars Asker; Henrik Boström; Panagiotis Papapetrou (SLDS, 2015)

Handling Small Calibration Sets in Mondrian Inductive Conformal Regressors. - Ulf Johansson; Ernst Ahlberg; Henrik Boström; Lars Carlsson; Henrik Linusson; Cecilia Sönströd (SLDS, 2015)

Forests of Randomized Shapelet Trees. - Isak Karlsson; Panagiotis Papapetrou; Henrik Boström (SLDS, 2015)

Post-analysis of multi-objective optimization solutions using decision trees. - Catarina Dudas; Amos H. C. Ng; Henrik Boström (Intell. Data Anal., 2015)

Bias reduction through conditional conformal prediction. - Tuve Löfström; Henrik Boström; Henrik Linusson; Ulf Johansson (Intell. Data Anal., 2015)

Predictive modeling of structured electronic health records for adverse drug event detection. - Jing Zhao 017; Aron Henriksson; Lars Asker; Henrik Boström (BMC Medical Informatics Decis. Mak., 2015)

Identifying Factors for the Effectiveness of Treatment of Heart Failure: A Registry Study. - Lars Asker; Henrik Boström; Panagiotis Papapetrou; Hans E. Persson (CBMS, 2016)

Evaluation of a Variance-Based Nonconformity Measure for Regression Forests. - Henrik Boström; Henrik Linusson; Tuve Löfström; Ulf Johansson (COPA, 2016)

Early Random Shapelet Forest. - Isak Karlsson; Panagiotis Papapetrou; Henrik Boström (DS, 2016)

Learning Decision Trees from Histogram Data Using Multiple Subsets of Bins. - Ram B. Gurung; Tony Lindgren; Henrik Boström (FLAIRS, 2016)

Predicting Adverse Drug Events Using Heterogeneous Event Sequences. - Isak Karlsson; Henrik Boström (ICHI, 2016)

Reliable Confidence Predictions Using Conformal Prediction. - Henrik Linusson; Ulf Johansson; Henrik Boström; Tuve Löfström (PAKDD (1), 2016)

Learning from Swedish Healthcare Data. - Lars Asker; Panagiotis Papapetrou; Henrik Boström (PETRA, 2016)

Clustering with Confidence: Finding Clusters with Statistical Guarantees. - Andreas Henelius; Kai Puolamäki; Henrik Boström; Panagiotis Papapetrou (CoRR, 2016)

Generalized random shapelet forests. - Isak Karlsson; Panagiotis Papapetrou; Henrik Boström (Data Min. Knowl. Discov., 2016)

Ensembles of randomized trees using diverse distributed representations of clinical events. - Aron Henriksson; Jing Zhao 017; Hercules Dalianis; Henrik Boström (BMC Medical Informatics Decis. Mak., 2016)

Using Conformal Prediction to Prioritize Compound Synthesis in Drug Discovery. - Ernst Ahlberg; Susanne Winiwarter; Henrik Boström; Henrik Linusson; Tuve Löfström; Ulf Norinder; Ulf Johansson; Ola Engkvist; Oscar Hammar; Claus Bendtsen; Lars Carlsson (COPA, 2017)

On the Calibration of Aggregated Conformal Predictors. - Henrik Linusson; Ulf Norinder; Henrik Boström; Ulf Johansson; Tuve Löfström (COPA, 2017)

Conformal Prediction Using Random Survival Forests. - Henrik Boström; Lars Asker; Ram B. Gurung; Isak Karlsson; Tony Lindgren; Panagiotis Papapetrou (ICMLA, 2017)

Model-agnostic nonconformity functions for conformal classification. - Ulf Johansson; Henrik Linusson; Tuve Löfström; Henrik Boström (IJCNN, 2017)

Mining disproportional itemsets for characterizing groups of heart failure patients from administrative health records. - Isak Karlsson; Panagiotis Papapetrou; Lars Asker; Henrik Boström; Hans E. Persson (PETRA, 2017)

Accelerating difficulty estimation for conformal regression forests. - Henrik Boström; Henrik Linusson; Tuve Löfström; Ulf Johansson (Ann. Math. Artif. Intell., 2017)

Learning from heterogeneous temporal data in electronic health records. - Jing Zhao 017; Panagiotis Papapetrou; Lars Asker; Henrik Boström (J. Biomed. Informatics, 2017)

Venn predictors for well-calibrated probability estimation trees. - Ulf Johansson; Tuwe Löfström; Håkan Sundell; Henrik Linusson; Anders Gidenstam; Henrik Boström (COPA, 2018)

Classification with Reject Option Using Conformal Prediction. - Henrik Linusson; Ulf Johansson; Henrik Boström; Tuve Löfström (PAKDD (1), 2018)

Exploring epistaxis as an adverse effect of anti-thrombotic drugs and outdoor temperature. - Jaakko Hollmén; Lars Asker; Isak Karlsson; Panagiotis Papapetrou; Henrik Boström; Birgitta Norstedt Wikner; Inger Öhman (PETRA, 2018)

Interpretable regression trees using conformal prediction. - Ulf Johansson; Henrik Linusson; Tuve Löfström; Henrik Boström (Expert Syst. Appl., 2018)

Gated Hidden Markov Models for Early Prediction of Outcome of Internet-Based Cognitive Behavioral Therapy. - Negar Safinianaini; Henrik Boström; Viktor Kaldo (AIME, 2019)

Predicting with Confidence from Survival Data. - Henrik Boström; Ulf Johansson; Anders Vesterberg (COPA, 2019)

Interpretable and specialized conformal predictors. - Ulf Johansson; Tuwe Löfström; Henrik Boström; Cecilia Sönströd (COPA, 2019)

Customized Interpretable Conformal Regressors. - Ulf Johansson; Cecilia Sönströd; Tuwe Löfström; Henrik Boström (DSAA, 2019)

Calibrating Probability Estimation Trees using Venn-Abers Predictors. - Ulf Johansson; Tuwe Löfström; Henrik Boström (SDM, 2019)

Block-distributed Gradient Boosted Trees. - Theodore Vasiloudis; Hyunsu Cho; Henrik Boström (SIGIR, 2019)

A study of data and label shift in the LIME framework. - Amir Hossein Akhavan Rahnama; Henrik Boström (CoRR, 2019)

Quantifying Uncertainty in Online Regression Forests. - Theodore Vasiloudis; Gianmarco De Francisci Morales; Henrik Boström (J. Mach. Learn. Res., 2019)

Conformal and probabilistic prediction with applications: editorial. - Alexander Gammerman; Vladimir Vovk; Henrik Boström; Lars Carlsson (Mach. Learn., 2019)

Efficient Venn predictors using random forests. - Ulf Johansson; Tuve Löfström; Henrik Linusson; Henrik Boström (Mach. Learn., 2019)

Mondrian conformal regressors. - Henrik Boström; Ulf Johansson (COPA, 2020)

Classication of aerosol particles using inductive conformal prediction. - Linn Karlsson; Henrik Boström; Paul Zieger (COPA, 2020)

Evaluating different approaches to calibrating conformal predictive systems. - Hugo Werner; Lars Carlsson; Ernst Ahlberg; Henrik Boström (COPA, 2020)

Explaining Multivariate Time Series Forecasts: An Application to Predicting the Swedish GDP. - Henrik Boström; Peter Höglund; Sven-Olof Junker; Ann-Sofie Öberg; Martin Sparr (XI-ML@KI, 2020)

Orthogonal Mixture of Hidden Markov Models. - Negar Safinianaini; Camila P. E. de Souza; Henrik Boström; Jens Lagergren (ECML/PKDD (1), 2020)

Study of Hellinger Distance as a splitting metric for Random Forests in balanced and imbalanced classification datasets. - Ricardo Aler; José María Valls; Henrik Boström (Expert Syst. Appl., 2020)

Efficient conformal predictor ensembles. - Henrik Linusson; Ulf Johansson; Henrik Boström (Neurocomputing, 2020)

Corrigendum to 'Learning from heterogeneous temporal data in electronic health records'. [J. Biomed. Inform. 65 (2017) 105-119]. - Jing Zhao 017; Panagiotis Papapetrou; Lars Asker; Henrik Boström (J. Biomed. Informatics, 2020)

Image Keypoint Matching Using Graph Neural Networks. - Nancy Xu; Giannis Nikolentzos; Michalis Vazirgiannis; Henrik Boström (COMPLEX NETWORKS, 2021)

Mondrian conformal predictive distributions. - Henrik Boström; Ulf Johansson; Tuwe Löfström (COPA, 2021)

Calibrating multi-class models. - Ulf Johansson; Tuwe Löfström; Henrik Boström (COPA, 2021)

Evaluation of updating strategies for conformal predictive systems in the presence of extreme events. - Hugo Werner; Lars Carlsson; Ernst Ahlberg; Henrik Boström (COPA, 2021)

Well-Calibrated and Sharp Interpretable Multi-Class Models. - Ulf Johansson; Tuwe Löfström; Henrik Boström (MDAI, 2021)

Investigating Normalized Conformal Regressors. - Ulf Johansson; Henrik Boström; Tuwe Löfström (SSCI, 2021)

Towards interpretability of Mixtures of Hidden Markov Models. - Negar Safinianaini; Henrik Boström (CoRR, 2021)

Evaluation of Local Model-Agnostic Explanations Using Ground Truth. - Amir Hossein Akhavan Rahnama; Judith Bütepage; Pierre Geurts; Henrik Boström (CoRR, 2021)

Assessing Explanation Quality by Venn Prediction. - Amr Alkhatib; Henrik Boström; Ulf Johansson (COPA, 2022)

crepes: a Python Package for Generating Conformal Regressors and Predictive Systems. - Henrik Boström (COPA, 2022)

Preface. - Ulf Johansson; Henrik Boström; Khuong An Nguyen; Zhiyuan Luo 001; Lars Carlsson (COPA, 2022)

Explaining Predictions by Characteristic Rules. - Amr Alkhatib; Henrik Boström; Michalis Vazirgiannis (ECML/PKDD (1), 2022)

Random subspace and random projection nearest neighbor ensembles for high dimensional data. - Sampath Deegalla; Keerthi Walgama; Panagiotis Papapetrou; Henrik Boström (Expert Syst. Appl., 2022)

Rule extraction with guarantees from regression models. - Ulf Johansson; Cecilia Sönströd; Tuwe Löfström; Henrik Boström (Pattern Recognit., 2022)

UnboundAttack: Generating Unbounded Adversarial Attacks to Graph Neural Networks. - Sofiane Ennadir; Amr Alkhatib; Giannis Nikolentzos; Michalis Vazirgiannis; Henrik Boström (COMPLEX NETWORKS (1), 2023)

Approximating Score-based Explanation Techniques Using Conformal Regression. - Amr Alkhatib; Henrik Boström; Sofiane Ennadir; Ulf Johansson (COPA, 2023)

Mondrian Predictive Systems for Censored Data. - Henrik Boström; Henrik Linusson; Anders Vesterberg (COPA, 2023)

Conformalized Adversarial Attack Detection for Graph Neural Networks. - Sofiane Ennadir; Amr Alkhatib; Henrik Boström; Michalis Vazirgiannis (COPA, 2023)

Investigating the Contribution of Privileged Information in Knowledge Transfer LUPI by Explainable Machine Learning. - Niharika Gauraha; Henrik Boström (COPA, 2023)

Confidence Classifiers with Guaranteed Accuracy or Precision. - Ulf Johansson; Cecilia Sönströd; Tuwe Löfström; Henrik Boström (COPA, 2023)

Tutorial on using Conformal Predictive Systems in KNIME. - Tuwe Löfström; Alexander Bondaletov; Artem Ryasik; Henrik Boström; Ulf Johansson (COPA, 2023)

A Simple and Yet Fairly Effective Defense for Graph Neural Networks. - Sofiane Ennadir; Yassine Abbahaddou; Johannes F. Lutzeyer; Michalis Vazirgiannis; Henrik Boström (AAAI, 2024)

Estimating Quality of Approximated Shapley Values Using Conformal Prediction. - Amr Alkhatib; Henrik Boström; Ulf Johansson (COPA, 2024)

Conformal Prediction in Python with crepes. - Henrik Boström (COPA, 2024)

Conformal Regression with Reject Option. - Ulf Johansson; Cecilia Sönströd; Henrik Boström (COPA, 2024)

CoPAL: Conformal Prediction in Active Learning An Algorithm for Enhancing Remaining Useful Life Estimation in Predictive Maintenance. - Zahra Kharazian; Tony Lindgren; Sindri Magnússon; Henrik Boström (COPA, 2024)

Interpretable Graph Neural Networks for Heterogeneous Tabular Data. - Amr Alkhatib; Henrik Boström (DS (1), 2024)

Faithfulness of Local Explanations for Tree-Based Ensemble Models. - Amir Hossein Akhavan Rahnama; Pierre Geurts; Henrik Boström (DS (2), 2024)

Interpretable Graph Neural Networks for Tabular Data. - Amr Alkhatib; Sofiane Ennadir; Henrik Boström; Michalis Vazirgiannis (ECAI, 2024)

Bounding the Expected Robustness of Graph Neural Networks Subject to Node Feature Attacks. - Yassine Abbahaddou; Sofiane Ennadir; Johannes F. Lutzeyer; Michalis Vazirgiannis; Henrik Boström (ICLR, 2024)

Example-Based Explanations of Random Forest Predictions. - Henrik Boström (IDA (2), 2024)

Fast Approximation of Shapley Values with Limited Data. - Amr Alkhatib; Henrik Boström (SCAI, 2024)

Local Point-wise Explanations of LambdaMART. - Amir Hossein Akhavan Rahnama; Judith Bütepage; Henrik Boström (SCAI, 2024)

Local List-Wise Explanations of LambdaMART. - Amir Hossein Akhavan Rahnama; Judith Bütepage; Henrik Boström (xAI (2), 2024)

Generating graph perturbations to enhance the generalization of GNNs. - Sofiane Ennadir; Giannis Nikolentzos; Michalis Vazirgiannis; Henrik Boström (AI Open, 2024)

Can local explanation techniques explain linear additive models? - Amir Hossein Akhavan Rahnama; Judith Bütepage; Pierre Geurts; Henrik Boström (Data Min. Knowl. Discov., 2024)

Testing Exchangeability for Multiple Sequences of P-values. - Henrik Boström (COPA, 2025)

Detect Adversarial Examples with Exchangeability Martingale. - Genghua Dong; Roman Bresson; Henrik Boström (COPA, 2025)

FlowGuard: Guarding Flow Matching via Conformal Sampling. - Ziyun Li; Henrik Boström (COPA, 2025)

Preface. - Harris Papadopoulos; Khuong An Nguyen; Zhiyuan Luo 001; Tuwe Löfström; Lars Carlsson; Henrik Boström (COPA, 2025)

Explaining Representations in Correlation-based Deep Multiview Representation Learning. - Maurice Kuschel; Amr Alkhatib; Tanuj Hasija; Henrik Boström (ICASSP, 2025)

Obtaining Example-Based Explanations from Deep Neural Networks. - Genghua Dong; Henrik Boström; Michalis Vazirgiannis; Roman Bresson (IDA, 2025)

Prediction via Shapley Value Regression. - Amr Alkhatib; Roman Bresson; Henrik Boström; Michalis Vazirgiannis (CoRR, 2025)