Alexander Karlsson

Orcid: 0000-0003-2973-3112

According to our database1, Alexander Karlsson authored at least 42 papers between 2008 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
Designing deep neural networks for driver intention recognition.
CoRR, 2024

2023
Low-Angle Target Tracking in Sea Surface Multipath Using Convolutional Neural Networks.
IEEE Trans. Aerosp. Electron. Syst., October, 2023

Topic modeling for anomaly detection in telecommunication networks.
J. Ambient Intell. Humaniz. Comput., 2023

Surrogate Deep Learning to Estimate Uncertainties for Driver Intention Recognition.
Proceedings of the 15th International Conference on Machine Learning and Computing, 2023

2021
Stepped Frequency Pulse Compression With Noncoherent Radar Using Deep Learning.
IEEE Trans. Aerosp. Electron. Syst., 2021

Multi-Machine Gaussian Topic Modeling for Predictive Maintenance.
IEEE Access, 2021

2020
Evaluation of Uncertainty Quantification in Deep Learning.
Proceedings of the Information Processing and Management of Uncertainty in Knowledge-Based Systems, 2020

2019
Deep Convolutional Neural Networks for the Prediction of Molecular Properties: Challenges and Opportunities Connected to the Data.
J. Integr. Bioinform., 2019

Deep Reinforcement Learning for Multiparameter Optimization in de novo Drug Design.
J. Chem. Inf. Model., 2019

Interactive Clustering for Exploring Multiple Data Streams at Different Time Scales and Granularity.
Proceedings of the Workshop on Interactive Data Mining, 2019

An Infinite Replicated Softmax Model for Topic Modeling.
Proceedings of the Modeling Decisions for Artificial Intelligence, 2019

Eliciting Structures in Data.
Proceedings of the Joint Proceedings of the ACM IUI 2019 Workshops co-located with the 24th ACM Conference on Intelligent User Interfaces (ACM IUI 2019), 2019

Artificial Intelligence.
Proceedings of the Data Science in Practice, 2019

Information Fusion.
Proceedings of the Data Science in Practice, 2019

Complex Data Analysis.
Proceedings of the Data Science in Practice, 2019

2018
Mode tracking using multiple data streams.
Inf. Fusion, 2018

On the behavior of the infinite restricted boltzmann machine for clustering.
Proceedings of the 33rd Annual ACM Symposium on Applied Computing, 2018

Improving the Use of Deep Convolutional Neural Networks for the Prediction of Molecular Properties.
Proceedings of the Practical Applications of Computational Biology and Bioinformatics, 2018

Evaluation of the Dirichlet Process Multinomial Mixture Model for Short-Text Topic Modeling.
Proceedings of the 6th International Symposium on Computational and Business Intelligence, 2018

Short Text Topic Modeling to Identify Trends on Wearable Bio-Sensors in Different Media Type.
Proceedings of the 6th International Symposium on Computational and Business Intelligence, 2018

A Self-Organizing Ensemble of Deep Neural Networks for the Classification of Data from Complex Processes.
Proceedings of the Information Processing and Management of Uncertainty in Knowledge-Based Systems. Applications, 2018

Situation Awareness in Telecommunication Networks Using Topic Modeling.
Proceedings of the 21st International Conference on Information Fusion, 2018

2017
Topic modeling for situation understanding in telecommunication networks.
Proceedings of the 27th International Telecommunication Networks and Applications Conference, 2017

A framework for identifying and evaluating technologies of interest for effective business strategy: Using text analytics to augment technology forecasting.
Proceedings of the 5th International Symposium on Computational and Business Intelligence, 2017

2016
Energy-efficient 5G deployment in rural areas.
Proceedings of the 12th IEEE International Conference on Wireless and Mobile Computing, 2016

Root-cause localization using Restricted Boltzmann Machines.
Proceedings of the 19th International Conference on Information Fusion, 2016

2015
Modeling uncertainty in bibliometrics and information retrieval: an information fusion approach.
Scientometrics, 2015

2014
Evidential Combination Operators for Entrapment Prediction in Advanced Driver Assistance Systems.
Proceedings of the Foundations of Intelligent Systems - 21st International Symposium, 2014

Decision Making with Hierarchical Credal Sets.
Proceedings of the Information Processing and Management of Uncertainty in Knowledge-Based Systems, 2014

2013
Uncertainty Levels of Second-Order Probability.
Polibits, 2013

Traceable Uncertainty for Threat Evaluation in Air to Ground Scenarios.
Proceedings of the Twelfth Scandinavian Conference on Artificial Intelligence, 2013

Traceable uncertainty.
Proceedings of the 16th International Conference on Information Fusion, 2013

2012
On Dependence in Second-Order Probability.
Proceedings of the Scalable Uncertainty Management - 6th International Conference, 2012

2011
Characterization and Empirical Evaluation of Bayesian and Credal Combination Operators.
J. Adv. Inf. Fusion, 2011

2010
Evaluating credal set theory as a belief framework in high-level information fusion for automated decision-making.
PhD thesis, 2010

An Empirical Comparison of Bayesian and Credal Set Theory for Discrete State Estimation.
Proceedings of the Information Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Methods, 2010

An empirical comparison of Bayesian and credal combination operators.
Proceedings of the 13th Conference on Information Fusion, 2010

Evaluating precise and imprecise State-Based Anomaly detectors for maritime surveillance.
Proceedings of the 13th Conference on Information Fusion, 2010

2008
Imprecise Probability as an Approach to Improved Dependability in High-Level Information Fusion.
Proceedings of the Interval / Probabilistic Uncertainty and Non-Classical Logics, 2008

A study on class-specifically discounted belief for ensemble classifiers.
Proceedings of the IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, 2008

An empirical comparison of Bayesian and credal networks for dependable high-level information fusion.
Proceedings of the 11th International Conference on Information Fusion, 2008

On evidential combination rules for ensemble classifiers.
Proceedings of the 11th International Conference on Information Fusion, 2008


  Loading...