Thorsteinn S. Rögnvaldsson

Publication Activity (10 Years)

Years Active: 1993-2024
Publications (10 Years): 33

Top Topics

Activity Recognition

Domain Adaptation

Top Venues

Data Min. Knowl. Discov.

Eng. Appl. Artif. Intell.

Publications

Abdallah Alabdallah, Mattias Ohlsson, Sepideh Pashami, Thorsteinn S. Rögnvaldsson
The Concordance Index decomposition: A measure for a deeper understanding of survival prediction models. Artif. Intell. Medicine 148 (2024)
Abdallah Alabdallah, Omar Hamed, Mattias Ohlsson, Thorsteinn S. Rögnvaldsson, Sepideh Pashami
CoxSE: Exploring the Potential of Self-Explaining Neural Networks with Cox Proportional Hazards Model for Survival Analysis. CoRR (2024)
Anna Vettoruzzo, Mohamed-Rafik Bouguelia, Thorsteinn S. Rögnvaldsson
Multimodal meta-learning through meta-learned task representations. Neural Comput. Appl. 36 (15) (2024)
Abdallah Alabdallah, Jakub Jakubowski, Sepideh Pashami, Szymon Bobek, Mattias Ohlsson, Thorsteinn S. Rögnvaldsson, Grzegorz J. Nalepa
Understanding Survival Models Through Counterfactual Explanations. ICCS (4) (2024)
Anna Vettoruzzo, Mohamed-Rafik Bouguelia, Thorsteinn S. Rögnvaldsson
Personalized Federated Learning with Contextual Modulation and Meta-Learning. SDM (2024)
Mohammed Ghaith Altarabichi, Abdallah Alabdallah, Sepideh Pashami, Thorsteinn S. Rögnvaldsson, Slawomir Nowaczyk, Mattias Ohlsson
Improving Concordance Index in Regression-based Survival Analysis: Evolutionary Discovery of Loss Function for Neural Networks. GECCO Companion (2024)
Anna Vettoruzzo, Mohamed-Rafik Bouguelia, Joaquin Vanschoren, Thorsteinn S. Rögnvaldsson, KC Santosh
Advances and Challenges in Meta-Learning: A Technical Review. IEEE Trans. Pattern Anal. Mach. Intell. 46 (7) (2024)
Emmanuella Budu, Kobra Etminani, Amira Soliman, Thorsteinn S. Rögnvaldsson
Evaluation of synthetic electronic health records: A systematic review and experimental assessment. Neurocomputing 603 (2024)
Anna Vettoruzzo, Mohamed-Rafik Bouguelia, Thorsteinn S. Rögnvaldsson
Meta-learning for efficient unsupervised domain adaptation. Neurocomputing 574 (2024)
Kunru Chen, Thorsteinn S. Rögnvaldsson, Slawomir Nowaczyk, Sepideh Pashami, Jonas Klang, Gustav Sternelöv
Material handling machine activity recognition by context ensemble with gated recurrent units. Eng. Appl. Artif. Intell. 126 (2023)
Felix Nilsson, Mohamed-Rafik Bouguelia, Thorsteinn S. Rögnvaldsson
Practical joint human-machine exploration of industrial time series using the matrix profile. Data Min. Knowl. Discov. 37 (1) (2023)
Emmanuella Budu, Amira Soliman, Kobra Etminani, Thorsteinn S. Rögnvaldsson
A Framework for Evaluating Synthetic Electronic Health Records. MIE (2023)
Reza Khoshkangini, Peyman Sheikholharam Mashhadi, Daniel Tegnered, Jens Lundström, Thorsteinn S. Rögnvaldsson
Predicting Vehicle Behavior Using Multi-task Ensemble Learning. Expert Syst. Appl. 212 (2023)
Anna Vettoruzzo, Mohamed-Rafik Bouguelia, Thorsteinn S. Rögnvaldsson
Personalized Federated Learning with Contextual Modulation and Meta-Learning. CoRR (2023)
Reza Khoshkangini, Mohsen Tajgardan, Peyman Sheikholharam Mashhadi, Thorsteinn S. Rögnvaldsson, Daniel Tegnered
Optimal Task Grouping Approach in Multitask Learning. ICONIP (6) (2023)
Hamid Sarmadi, Thorsteinn S. Rögnvaldsson, Nils Roger Carlsson, Mattias Ohlsson, Ibrahim Wahab, Ola Hall
Towards Explaining Satellite Based Poverty Predictions with Convolutional Neural Networks. CoRR (2023)
Anna Vettoruzzo, Mohamed-Rafik Bouguelia, Thorsteinn S. Rögnvaldsson
Meta-Learning from Multimodal Task Distributions Using Multiple Sets of Meta-Parameters. IJCNN (2023)
Anna Vettoruzzo, Mohamed-Rafik Bouguelia, Joaquin Vanschoren, Thorsteinn S. Rögnvaldsson, KC Santosh
Advances and Challenges in Meta-Learning: A Technical Review. CoRR (2023)
Hamid Sarmadi, Thorsteinn S. Rögnvaldsson, Nils Roger Carlsson, Mattias Ohlsson, Ibrahim Wahab, Ola Hall
Towards Explaining Satellite Based Poverty Predictions with Convolutional Neural Networks. DSAA (2023)
Kunru Chen, Thorsteinn S. Rögnvaldsson, Slawomir Nowaczyk, Sepideh Pashami, Jonas Klang, Gustav Sternelöv
Toward Solving Domain Adaptation with Limited Source Labeled Data. ICDM (Workshops) (2023)
Abdallah Alabdallah, Mattias Ohlsson, Sepideh Pashami, Thorsteinn S. Rögnvaldsson
The Concordance Index decomposition: a measure for a deeper understanding of survival prediction models. CoRR (2022)
Kunru Chen, Thorsteinn S. Rögnvaldsson, Slawomir Nowaczyk, Sepideh Pashami, Emilia Johansson, Gustav Sternelöv
Semi-Supervised Learning for Forklift Activity Recognition from Controller Area Network (CAN) Signals. Sensors 22 (11) (2022)
Ola Hall, Mattias Ohlsson, Thorsteinn S. Rögnvaldsson
Satellite Image and Machine Learning based Knowledge Extraction in the Poverty and Welfare Domain. CoRR (2022)
Abdallah Alabdallah, Sepideh Pashami, Thorsteinn S. Rögnvaldsson, Mattias Ohlsson
SurvSHAP: A Proxy-Based Algorithm for Explaining Survival Models with SHAP. DSAA (2022)
Ola Hall, Mattias Ohlsson, Thorsteinn S. Rögnvaldsson
A review of explainable AI in the satellite data, deep machine learning, and human poverty domain. Patterns 3 (10) (2022)
Jennifer David, Thorsteinn S. Rögnvaldsson, Bo Söderberg, Mattias Ohlsson
Deterministic annealing with Potts neurons for multi-robot routing. Intell. Serv. Robotics 15 (3) (2022)
Jennifer David, Thorsteinn S. Rögnvaldsson
Multi-Robot Routing Problem with Min-Max Objective. Robotics 10 (4) (2021)
Kunru Chen, Sepideh Pashami, Slawomir Nowaczyk, Emilia Johansson, Gustav Sternelöv, Thorsteinn S. Rögnvaldsson
Forklift Truck Activity Recognition from CAN Data. IoT Streams/ITEM@PKDD/ECML (2020)
Yuantao Fan, Slawomir Nowaczyk, Thorsteinn S. Rögnvaldsson
Transfer learning for remaining useful life prediction based on consensus self-organizing models. Reliab. Eng. Syst. Saf. 203 (2020)
Yuantao Fan, Slawomir Nowaczyk, Thorsteinn S. Rögnvaldsson
Transfer learning for Remaining Useful Life Prediction Based on Consensus Self-Organizing Models. CoRR (2019)
Thorsteinn S. Rögnvaldsson, Slawomir Nowaczyk, Stefan Byttner, Rune Prytz, Magnus Svensson
Self-monitoring for maintenance of vehicle fleets. Data Min. Knowl. Discov. 32 (2) (2018)
Thorsteinn S. Rögnvaldsson, Antanas Verikas, Josef Bigün, Slawomir Nowaczyk, Anita Pinheiro Sant'Anna, Björn Åstrand, Jens Lundström, Stefan Byttner, Roland Thörner, Fernando Alonso-Fernandez, Martin Cooney, Rafael Valencia
Center for Applied Intelligent Systems Research (Position paper). SAIS (2016)
Iulian Carpatorea, Slawomir Nowaczyk, Thorsteinn S. Rögnvaldsson, Marcus Elmer, Johan Lodin
Learning of Aggregate Features for Comparing Drivers Based on Naturalistic Data. ICMLA (2016)
Yuantao Fan, Slawomir Nowaczyk, Thorsteinn S. Rögnvaldsson
Evaluation of Self-Organized Approach for Predicting Compressor Faults in a City Bus Fleet. INNS Conference on Big Data (2015)
Rune Prytz, Slawomir Nowaczyk, Thorsteinn S. Rögnvaldsson, Stefan Byttner
Predicting the need for vehicle compressor repairs using maintenance records and logged vehicle data. Eng. Appl. Artif. Intell. 41 (2015)
Thorsteinn S. Rögnvaldsson, Liwen You, Daniel Garwicz
State of the art prediction of HIV-1 protease cleavage sites. Bioinform. 31 (8) (2015)
Yuantao Fan, Slawomir Nowaczyk, Thorsteinn S. Rögnvaldsson
Incorporating Expert Knowledge into a Self-Organized Approach for Predicting Compressor Faults in a City Bus Fleet. SCAI (2015)
Thorsteinn S. Rögnvaldsson, Henrik Norrman, Stefan Byttner, Eric Järpe
Estimating p-Values for Deviation Detection. SASO (2014)
Slawomir Nowaczyk, Rune Prytz, Thorsteinn S. Rögnvaldsson, Stefan Byttner
Towards a Machine Learning Algorithm for Predicting Truck Compressor Failures Using Logged Vehicle Data. SCAI (2013)
Henrik Andreasson, Abdelbaki Bouguerra, Björn Åstrand, Thorsteinn S. Rögnvaldsson
Gold-Fish SLAM: An Application of SLAM to Localize AGVs. FSR (2012)
Stefan Byttner, Thorsteinn S. Rögnvaldsson, Magnus Svensson
Consensus self-organized models for fault detection (COSMO). Eng. Appl. Artif. Intell. 24 (5) (2011)
Stefan Byttner, Magnus Svensson, Thorsteinn S. Rögnvaldsson
Finding the Odd-One-Out in Fleets of Mechatronic Systems using Embedded Intelligent Agents. AAAI Spring Symposium: Embedded Reasoning (2010)
Stefan Byttner, Thorsteinn S. Rögnvaldsson, Magnus Svensson, George Bitar, Wesley Chominsky
Networked Vehicles for Automated Fault Detection. ISCAS (2009)
Thorsteinn S. Rögnvaldsson, Terence A. Etchells, Liwen You, Daniel Garwicz, Ian H. Jarman, Paulo J. G. Lisboa
How to find simple and accurate rules for viral protease cleavage specificities. BMC Bioinform. 10 (2009)
Abdelbaki Bouguerra, Henrik Andreasson, Achim J. Lilienthal, Björn Åstrand, Thorsteinn S. Rögnvaldsson
An Autonomous Robotic System for Load Transportation. ETFA (2009)
Thorsteinn S. Rögnvaldsson, Georg Panholzer, Stefan Byttner, Magnus Svensson
A self-organized approach for unsupervised fault detection in multiple systems. ICPR (2008)
Liwen You, Thorsteinn S. Rögnvaldsson
Almost Linear Biobasis Function Neural Networks. IJCNN (2007)
Kenneth Nilsson, Thorsteinn S. Rögnvaldsson, Jens Cameron, Christina Jacobson
Biometric Identification of Mice. ICPR (4) (2006)
Eric A. Antonelo, Albert-Jan Baerveldt, Thorsteinn S. Rögnvaldsson, Maurício F. Figueiredo
Modular Neural Network and Classical Reinforcement Learning for Autonomous Robot Navigation: Inhibiting Undesirable Behaviors. IJCNN (2006)
Thorsteinn S. Rögnvaldsson, Liwen You
Why neural networks should not be used for HIV-1 protease cleavage site prediction. Bioinform. 20 (11) (2004)
Jim Samuelsson, Daniel Dalevi, Fredrik Levander, Thorsteinn S. Rögnvaldsson
Modular, scriptable and automated analysis tools for high-throughput peptide mass fingerprinting. Bioinform. 20 (18) (2004)
John E. Moody, Thorsteinn S. Rögnvaldsson
Smoothing Regularizers for Projective Basis Function Networks. NIPS (1996)
Thorsteinn S. Rögnvaldsson
On Langevin Updating in Multilayer Perceptrons. Neural Comput. 6 (5) (1994)
Thorsteinn S. Rögnvaldsson
Pattern Discrimination Using Feedforward Networks: A Benchmark Study of Scaling Behavior. Neural Comput. 5 (3) (1993)