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ORCIDErik Strumbelj
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2020 – today
- 2024
[i4]Valter Hudovernik, Martin Jurkovic, Erik Strumbelj:
Benchmarking the Fidelity and Utility of Synthetic Relational Data. CoRR abs/2410.03411 (2024)- 2022
- [j15]Gregor Pirs
, Erik Strumbelj:
Bayesian Gaussian process factor analysis with copula for count data. Expert Syst. Appl. 197: 116645 (2022) - 2021
- [i3]Andraz De Luisa, Jan Hartman, David Nabergoj, Samo Pahor, Marko Rus, Bozhidar Stevanoski, Jure Demsar, Erik Strumbelj:
Predicting the Popularity of Games on Steam. CoRR abs/2110.02896 (2021) - 2020
- [j14]Petar Vracar, Erik Strumbelj, Igor Kononenko:
Automatic attribute construction for basketball modelling. Knowl. Inf. Syst. 62(2): 541-570 (2020) - [c7]Matija Rezar, Erik Strumbelj, Giacomo Pojani, Chris Marshall:
Opportunistic Positioning Using Unsynchronized References: Crowd Systems - Smartphones: Signals of opportunity, cellular systems (4G, 5G, WLAN, ...). ENC 2020: 1-10 - [c6]Tadej Ciglaric, Rok Cesnovar, Erik Strumbelj:
Automated OpenCL GPU kernel fusion for Stan Math. IWOCL 2020: 14:1-14:6
2010 – 2019
- 2019
- [j13]Gregor Pirs, Erik Strumbelj:
Bayesian Combination of Probabilistic Classifiers using Multivariate Normal Mixtures. J. Mach. Learn. Res. 20: 51:1-51:18 (2019) - [j12]Rok Ciglic, Erik Strumbelj, Rok Cesnovar, Mauro Hrvatin, Drago Perko:
Evaluating existing manually constructed natural landscape classification with a machine learning-based approach. J. Spatial Inf. Sci. 18(1): 31-56 (2019) - [j11]Tadej Ciglaric, Rok Cesnovar, Erik Strumbelj:
An OpenCL library for parallel random number generators. J. Supercomput. 75(7): 3866-3881 (2019) - [i2]Rok Cesnovar, Steve Bronder, Davor Sluga, Jure Demsar, Tadej Ciglaric, Sean Talts, Erik Strumbelj:
GPU-based Parallel Computation Support for Stan. CoRR abs/1907.01063 (2019) - [i1]Jure Demsar, Grega Repovs, Erik Strumbelj:
bayes4psy - an Open Source R Package for Bayesian Statistics in Psychology. CoRR abs/1907.01952 (2019) - 2018
- [j10]Jana Faganeli Pucer, Gregor Pirs, Erik Strumbelj:
A Bayesian approach to forecasting daily air-pollutant levels. Knowl. Inf. Syst. 57(3): 635-654 (2018) - [p1]Erik Strumbelj, Igor Kononenko:
Explaining the Predictions of an Arbitrary Prediction Model: Feature Contributions and Quasi-nomograms. Human and Machine Learning 2018: 139-157 - 2016
- [j9]Petar Vracar, Erik Strumbelj, Igor Kononenko:
Modeling basketball play-by-play data. Expert Syst. Appl. 44: 58-66 (2016) - 2015
- [j8]Erik Strumbelj, Marko Robnik-Sikonja:
Predictive power of fantasy sports data for soccer forecasting. Int. J. Data Min. Model. Manag. 7(2): 154-163 (2015) - 2014
- [j7]Erik Strumbelj, Igor Kononenko:
Explaining prediction models and individual predictions with feature contributions. Knowl. Inf. Syst. 41(3): 647-665 (2014) - 2013
- [j6]Marko Robnik-Sikonja, Erik Strumbelj, Igor Kononenko:
Efficiently explaining the predictions of a probabilistic radial basis function classification network. Intell. Data Anal. 17(5): 791-802 (2013) - [j5]Igor Kononenko, Erik Strumbelj, Zoran Bosnic, Darko Pevec, Matjaz Kukar, Marko Robnik-Sikonja:
Explanation and Reliability of Individual Predictions. Informatica (Slovenia) 37(1): 41-48 (2013) - 2012
- [j4]Marko Robnik-Sikonja, Igor Kononenko, Erik Strumbelj:
Quality of classification explanations with PRBF. Neurocomputing 96: 37-46 (2012) - 2011
- [c5]Erik Strumbelj, Igor Kononenko:
A General Method for Visualizing and Explaining Black-Box Regression Models. ICANNGA (2) 2011: 21-30 - [c4]Darko Pevec, Erik Strumbelj, Igor Kononenko:
Evaluating Reliability of Single Classifications of Neural Networks. ICANNGA (1) 2011: 22-30 - [c3]Marko Robnik-Sikonja, Aristidis Likas, Constantinos Constantinopoulos, Igor Kononenko, Erik Strumbelj:
Efficiently Explaining Decisions of Probabilistic RBF Classification Networks. ICANNGA (1) 2011: 169-179 - 2010
- [j3]Erik Strumbelj, Igor Kononenko:
An Efficient Explanation of Individual Classifications using Game Theory. J. Mach. Learn. Res. 11: 1-18 (2010) - [j2]Erik Strumbelj, Zoran Bosnic, Igor Kononenko, Branko Zakotnik, Cvetka Grasic Kuhar:
Explanation and reliability of prediction models: the case of breast cancer recurrence. Knowl. Inf. Syst. 24(2): 305-324 (2010)
2000 – 2009
- 2009
- [j1]Erik Strumbelj, Igor Kononenko, Marko Robnik-Sikonja:
Explaining instance classifications with interactions of subsets of feature values. Data Knowl. Eng. 68(10): 886-904 (2009) - [c2]Erik Strumbelj, Marko Robnik-Sikonja, Igor Kononenko:
Learning Betting Tips from Users' Bet Selections. MLDM 2009: 678-688 - 2008
- [c1]Erik Strumbelj, Igor Kononenko:
Towards a Model Independent Method for Explaining Classification for Individual Instances. DaWaK 2008: 273-282
Coauthor Index
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