| Talking probabilities: communicating probabilistic information with words and numbers S Renooij, CLM Witteman International Journal of Approximate Reasoning 22, 169 – 194, 1999 | 297 | 1999 |
| Probability elicitation for belief networks: issues to consider S Renooij The Knowledge Engineering Review 16 (3), 255-269, 2001 | 267 | 2001 |
| Probabilities for a probabilistic network: a case study in oesophageal cancer LC Van der Gaag, S Renooij, CLM Witteman, BMP Aleman, BG Taal Artificial Intelligence in medicine 25 (2), 123-148, 2002 | 250 | 2002 |
| How to elicit many probabilities LC van der Gaag, S Renooij, CLM Witteman, BMP Aleman, BG Taal Fifteenth Conference on Uncertainty in Artificial Intelligence, 647 – 654, 1999 | 206* | 1999 |
| A method for explaining Bayesian networks for legal evidence with scenarios CS Vlek, H Prakken, S Renooij, B Verheij Artificial Intelligence and Law 24 (3), 285-324, 2016 | 111 | 2016 |
| Evaluation of a verbal–numerical probability scale C Witteman, S Renooij International Journal of Approximate Reasoning 33 (2), 117-131, 2003 | 111 | 2003 |
| A two-phase method for extracting explanatory arguments from Bayesian networks ST Timmer, JJC Meyer, H Prakken, S Renooij, B Verheij International Journal of Approximate Reasoning 80, 475-494, 2017 | 101 | 2017 |
| Arguments, scenarios and probabilities: connections between three normative frameworks for evidential reasoning B Verheij, F Bex, ST Timmer, CS Vlek, JJC Meyer, S Renooij, H Prakken Law, Probability and Risk 15 (1), 35-70, 2016 | 96 | 2016 |
| Building Bayesian networks for legal evidence with narratives: a case study evaluation CS Vlek, H Prakken, S Renooij, B Verheij Artificial intelligence and law 22 (4), 375-421, 2014 | 84 | 2014 |
| Sensitivity analysis of probabilistic networks LC Van der Gaag, S Renooij, VMH Coupé Advances in probabilistic graphical models, 103-124, 2021 | 79 | 2021 |
| Analysing sensitivity data from probabilistic networks LC van der Gaag, S Renooij Proceedings of the Seventeenth Conference on Uncertainty in Artificial …, 2001 | 66* | 2001 |
| From qualitative to quantitative probabilistic networks S Renooij, LC van der Gaag Proceedings of the Eighteenth Conference on Uncertainty in Artificial …, 2002 | 64* | 2002 |
| Qualitative approaches to quantifying probabilistic networks S Renooij Utrecht University, 2001 | 60 | 2001 |
| Context-specific sign-propagation in qualitative probabilistic networks S Renooij, LC Van der Gaag, S Parsons Artificial Intelligence 140 (1-2), 207-230, 2002 | 58 | 2002 |
| Discretizing environmental data for learning Bayesian-network classifiers RF Ropero, S Renooij, LC Van der Gaag Ecological Modelling 368, 391-403, 2018 | 53 | 2018 |
| Modeling crime scenarios in a Bayesian network C Vlek, H Prakken, S Renooij, B Verheij Proceedings of the fourteenth international conference on artificial …, 2013 | 51 | 2013 |
| Explaining Bayesian networks using argumentation ST Timmer, JJC Meyer, H Prakken, S Renooij, B Verheij European Conference on Symbolic and Quantitative Approaches to Reasoning and …, 2015 | 46 | 2015 |
| Enhancing QPNs for trade-off resolution S Renooij, LC van der Gaag Fifteenth Conference on Uncertainty in Artificial Intelligence, 559 – 566, 1999 | 43* | 1999 |
| Enhanced qualitative probabilistic networks for resolving trade-offs S Renooij, LC Van Der Gaag Artificial Intelligence 172 (12-13), 1470-1494, 2008 | 40 | 2008 |
| Reconstructing causal reasoning about evidence: a case study H Prakken, S Renooij Legal knowledge and information systems. JURIX, 131-142, 2001 | 39 | 2001 |
Linda C. van der GaagSenior researcher, Dalle Molle Institute for Artificial Intelligence Research, Lugano, SwitzerlandVerified email at idsia.ch
