Anytime inductive logic programming. - Tony Lindgren (CATA, 2000)

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

Methods for Rule Conflict Resolution. - Tony Lindgren (ECML, 2004)

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

On handling conflicts between rules with numerical features. - Tony Lindgren (SAC, 2006)

Troubleshooting ECU Programmed by Bodybuilders. - Tony Lindgren (ICCVE, 2012)

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

Randomized Separate and Conquer Rule induction. - Tony Lindgren (ICCDA, 2017)

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

On Data Driven Organizations and the Necessity of Interpretable Models. - Tony Lindgren (SGIoT, 2018)

Example-Based Feature Tweaking Using Random Forests. - Tony Lindgren; Panagiotis Papapetrou; Isak Samsten; Lars Asker (IRI, 2019)

A Methodology for Prognostics Under the Conditions of Limited Failure Data Availability. - Gishan Don Ranasinghe; Tony Lindgren; Mark Girolami; Ajith Kumar Parlikad (IEEE Access, 2019)

Evaluation of Dimensionality Reduction Techniques-Principal Feature Analysis in case of Text Classification Problems. - Michael Mammo; Tony Lindgren (ICCDE, 2020)

Z-Miner: An Efficient Method for Mining Frequent Arrangements of Event Intervals. - Zed Lee; Tony Lindgren; Panagiotis Papapetrou (KDD, 2020)

Prediction of Global Navigation Satellite System Positioning Errors with Guarantees. - Alejandro Kuratomi; Tony Lindgren; Panagiotis Papapetrou (ECML/PKDD (4), 2020)

Hybrid feature tweaking: Combining random forest similarity tweaking with CLPFD. - Tony Mattias Lindgren (ICCDE, 2021)

Z-Hist: A Temporal Abstraction of Multivariate Histogram Snapshots. - Zed Lee; Nicholas Anton; Panagiotis Papapetrou; Tony Lindgren (IDA, 2021)

JUICE: JUstIfied Counterfactual Explanations. - Alejandro Kuratomi; Ioanna Miliou; Zed Lee; Tony Lindgren; Panagiotis Papapetrou (DS, 2022)

Low dimensional synthetic data generation for improving data driven prognostic models. - Tony Lindgren; Olof Steinert (ICPHM, 2022)

Measuring the Burden of (Un)fairness Using Counterfactuals. - Alejandro Kuratomi; Evaggelia Pitoura; Panagiotis Papapetrou; Tony Lindgren; Panayiotis Tsaparas (PKDD/ECML Workshops (1), 2022)

Knowledge Transfer in Engineering Fleets: Hierarchical Bayesian Modelling for Multi-Task Learning. - Lawrence A. Bull; Maharshi Harshadbhai Dhada; Olof Steinert; Tony Lindgren; Ajith Kumar Parlikad; Andrew B. Duncan; Mark Girolami (CoRR, 2022)

Automotive Multilingual Fault Diagnosis. - John Pavlopoulos; Alv Romell; Jacob Curman; Olof Steinert; Tony Lindgren; Markus Borg (CoRR, 2022)

ORANGE: Opposite-label soRting for tANGent Explanations in heterogeneous spaces. - Alejandro Kuratomi; Zed Lee; Ioanna Miliou; Tony Lindgren; Panagiotis Papapetrou (DSAA, 2023)

Robust Contrastive Learning and Multi-shot Voting for High-dimensional Multivariate Data-driven Prognostics. - Kaiji Sun; Sindri Magnússon; Olof Steinert; Tony Lindgren (ICPHM, 2023)

AID4HAI: Automatic Idea Detection for Healthcare-Associated Infections from Twitter, a Framework Based on Active Learning and Transfer Learning. - Zahra Kharazian; Mahmoud Rahat; Fábio F. Gama; Peyman Sheikholharam Mashhadi; Slawomir Nowaczyk; Tony Lindgren; Sindri Magnússon (IDA, 2023)

Hierarchical Bayesian modeling for knowledge transfer across engineering fleets via multitask learning. - Lawrence A. Bull; Domenic Di Francesco; Maharshi Harshadbhai Dhada; Olof Steinert; Tony Lindgren; Ajith Kumar Parlikad; Andrew B. Duncan; Mark Girolami (Comput. Aided Civ. Infrastructure Eng., 2023)

Weibull recurrent neural networks for failure prognosis using histogram data. - Maharshi Harshadbhai Dhada; Ajith Kumar Parlikad; Olof Steinert; Tony Lindgren (Neural Comput. Appl., 2023)

CICLe: Conformal In-Context Learning for Largescale Multi-Class Food Risk Classification. - Korbinian Randl; John Pavlopoulos; Aron Henriksson; Tony Lindgren (ACL (Findings), 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)

Evaluating the Reliability of Self-explanations in Large Language Models. - Korbinian Randl; John Pavlopoulos; Aron Henriksson; Tony Lindgren (DS (1), 2024)

SHAP-Driven Explainability in Survival Analysis for Predictive Maintenance Applications. - Monireh Kargar; Zahra Kharazian; Ioanna Miliou; Tony Lindgren (HAII5.0@ECAI, 2024)

CounterFair: Group Counterfactuals for Bias Detection, Mitigation and Subgroup Identification. - Alejandro Kuratomi; Zed Lee; Panayiotis Tsaparas; Guilherme Dinis Junior; Evaggelia Pitoura; Tony Lindgren; Panagiotis Papapetrou (ICDM, 2024)

SCANIA Component X Dataset: A Real-World Multivariate Time Series Dataset for Predictive Maintenance. - Zahra Kharazian; Tony Lindgren; Sindri Magnússon; Olof Steinert; Oskar Andersson Reyna (CoRR, 2024)

A Cost-Sensitive Transformer Model for Prognostics Under Highly Imbalanced Industrial Data. - Ali Beikmohammadi; Mohammad Hosein Hamian; Neda Khoeyniha; Tony Lindgren; Olof Steinert; Sindri Magnússon (CoRR, 2024)

A Strategy Fusion-Based Multiobjective Optimization Approach for Agile Earth Observation Satellite Scheduling Problem. - He Wang; Weiquan Huang; Sindri Magnússon; Tony Lindgren; Ran Wang; Yanjie Song 001 (IEEE Trans. Geosci. Remote. Sens., 2024)

Z-Time: efficient and effective interpretable multivariate time series classification. - Zed Lee; Tony Lindgren; Panagiotis Papapetrou (Data Min. Knowl. Discov., 2024)

Automotive fault nowcasting with machine learning and natural language processing. - John Pavlopoulos; Alv Romell; Jacob Curman; Olof Steinert; Tony Lindgren; Markus Borg; Korbinian Randl (Mach. Learn., 2024)

Ijuice: integer JUstIfied counterfactual explanations. - Alejandro Kuratomi; Ioanna Miliou; Zed Lee; Tony Lindgren; Panagiotis Papapetrou (Mach. Learn., 2024)

SemEval-2025 Task 9: The Food Hazard Detection Challenge. - Korbinian Randl; John Pavlopoulos; Aron Henriksson; Tony Lindgren; Juli Bakagianni (CoRR, 2025)

CRITS: Convolutional Rectifier for Interpretable Time Series Classification. - Alejandro Kuratomi; Zed Lee; Guilherme Dinis Junior; Tony Lindgren; Diego García-Pérez (CoRR, 2025)