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Marek J. Druzdzel
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- affiliation: University of Pittsburgh, Pennsylvania, USA
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2020 – today
- 2021
- [j20]Sanya Bathla Taneja
, Gerald P. Douglas, Gregory F. Cooper, Marian G. Michaels, Marek J. Druzdzel, Shyam Visweswaran:
Bayesian network models with decision tree analysis for management of childhood malaria in Malawi. BMC Medical Informatics Decis. Mak. 21(1): 158 (2021)
2010 – 2019
- 2019
- [j19]Jidapa Kraisangka, Marek J. Druzdzel:
Corrigendum to "A Bayesian network interpretation of the Cox's proportional hazard model" [Int. J. Approx. Reason. 103 (2018) 195-211]. Int. J. Approx. Reason. 111: 51-52 (2019) - [c60]Jidapa Kraisangka, Marek J. Druzdzel, Lisa C. Lohmueller, Manreet K. Kanwar
Bayesian Network vs. Cox's Proportional Hazard Model of PAH Risk: A Comparison. AIME 2019: 139-149 - [c59]Dmitriy Babichenko, Marek J. Druzdzel, Neal Benedict
Moving Beyond Branching: Evaluating Educational Impact of Procedurally-Generated Virtual Patients. SeGAH 2019: 1-8 - 2018
- [j18]Jidapa Kraisangka, Marek J. Druzdzel:
A Bayesian network interpretation of the Cox's proportional hazard model. Int. J. Approx. Reason. 103: 195-211 (2018) - 2017
- [j17]Mario A. Cypko, Matthaeus Stoehr, Marcin Kozniewski
Validation workflow for a clinical Bayesian network model in multidisciplinary decision making in head and neck oncology treatment. Int. J. Comput. Assist. Radiol. Surg. 12(11): 1959-1970 (2017) - 2016
- [j16]Adam Zagorecki
Modeling women's menstrual cycles using PICI gates in Bayesian network. Int. J. Approx. Reason. 70: 123-136 (2016) - [c58]Jidapa Kraisangka, Marek J. Druzdzel:
Making Large Cox's Proportional Hazard Models Tractable in Bayesian Networks. Probabilistic Graphical Models 2016: 252-263 - [c57]Dmitriy Babichenko, Marek J. Druzdzel, Lorin Grieve, Ravi Patel, Jonathan Velez, Taylor Neal, James McCray, Rae-Djamaal Wallace, Sean Jenkins:
Designing the model patient: Data-driven virtual patients in medical education. SeGAH 2016: 1-8 - [c56]Jidapa Kraisangka, Marek J. Druzdzel, Raymond L. Benza:
A Risk Calculator for the Pulmonary Arterial Hypertension Based on a Bayesian Network. BMA@UAI 2016: 1-6 - 2015
- [j15]Parot Ratnapinda
Learning discrete Bayesian network parameters from continuous data streams: What is the best strategy? J. Appl. Log. 13(4): 628-642 (2015) - [c55]Adam Zagorecki, Marcin Kozniewski, Marek J. Druzdzel:
An Approximation of Surprise Index as a Measure of Confidence. AAAI Fall Symposia 2015: 39- - [p2]Agnieszka Onisko, Allan Tucker, Marek J. Druzdzel:
Prediction and Prognosis of Health and Disease. Foundations of Biomedical Knowledge Representation 2015: 181-188 - [p1]Anna Lupinska-Dubicka, Marek J. Druzdzel:
Modeling Dynamic Processes with Memory by Higher Order Temporal Models. Foundations of Biomedical Knowledge Representation 2015: 219-232 - 2014
- [c54]Parot Ratnapinda, Marek J. Druzdzel:
An Empirical Evaluation of Costs and Benefits of Simplifying Bayesian Networks by Removing Weak Arcs. FLAIRS 2014 - [c53]Agnieszka Onisko, Marek J. Druzdzel:
Impact of Bayesian Network Model Structure on the Accuracy of Medical Diagnostic Systems. ICAISC (2) 2014: 167-178 - [c52]Martijn de Jongh, Marek J. Druzdzel:
Evaluation of Rules for Coping with Insufficient Data in Constraint-Based Search Algorithms. Probabilistic Graphical Models 2014: 190-205 - [c51]Jidapa Kraisangka, Marek J. Druzdzel:
Discrete Bayesian Network Interpretation of the Cox's Proportional Hazards Model. Probabilistic Graphical Models 2014: 238-253 - [c50]Krzysztof Nowak, Marek J. Druzdzel:
Learning Parameters in Canonical Models Using Weighted Least Squares. Probabilistic Graphical Models 2014: 366-381 - 2013
- [j14]Agnieszka Onisko, Marek J. Druzdzel
Impact of precision of Bayesian network parameters on accuracy of medical diagnostic systems. Artif. Intell. Medicine 57(3): 197-206 (2013) - [j13]Adam Zagorecki, Marek J. Druzdzel
Knowledge Engineering for Bayesian Networks: How Common Are Noisy-MAX Distributions in Practice? IEEE Trans. Syst. Man Cybern. Syst. 43(1): 186-195 (2013) - [c49]Parot Ratnapinda, Marek J. Druzdzel:
An Empirical Comparison of Bayesian Network Parameter Learning Algorithms for Continuous Data Streams. FLAIRS 2013 - [i17]Jian Cheng, Marek J. Druzdzel:
Confidence Inference in Bayesian Networks. CoRR abs/1301.2260 (2013) - [i16]Jian Cheng, Marek J. Druzdzel:
Computational Investigation of Low-Discrepancy Sequences in Simulation Algorithms for Bayesian Networks. CoRR abs/1301.3841 (2013) - [i15]Tsai-Ching Lu, Marek J. Druzdzel, Tze-Yun Leong:
Causal Mechanism-based Model Construction. CoRR abs/1301.3872 (2013) - [i14]Haiqin Wang, Marek J. Druzdzel:
User Interface Tools for Navigation in Conditional Probability Tables and Elicitation of Probabilities in Bayesian Networks. CoRR abs/1301.4430 (2013) - [i13]Denver Dash, Marek J. Druzdzel:
A Hybrid Anytime Algorithm for the Constructiion of Causal Models From Sparse Data. CoRR abs/1301.6689 (2013) - [i12]Yan Lin, Marek J. Druzdzel:
Computational Advantages of Relevance Reasoning in Bayesian Belief Networks. CoRR abs/1302.1558 (2013) - [i11]Marek J. Druzdzel, Linda C. van der Gaag:
Elicitation of Probabilities for Belief Networks: Combining Qualitative and Quantitative Information. CoRR abs/1302.4943 (2013) - [i10]Marek J. Druzdzel:
Some Properties of Joint Probability Distributions. CoRR abs/1302.6802 (2013) - [i9]Marek J. Druzdzel, Herbert A. Simon:
Causality in Bayesian Belief Networks. CoRR abs/1303.1454 (2013) - [i8]Marek J. Druzdzel, Max Henrion:
Intercausal Reasoning with Uninstantiated Ancestor Nodes. CoRR abs/1303.1492 (2013) - [i7]Max Henrion, Marek J. Druzdzel:
Qualitative Propagation and Scenario-based Explanation of Probabilistic Reasoning. CoRR abs/1304.1082 (2013) - 2012
- [i6]Mark Voortman, Denver Dash, Marek J. Druzdzel:
Learning Why Things Change: The Difference-Based Causality Learner. CoRR abs/1203.3525 (2012) - [i5]Changhe Yuan, Marek J. Druzdzel:
Importance Sampling in Bayesian Networks: An Influence-Based Approximation Strategy for Importance Functions. CoRR abs/1207.1422 (2012) - [i4]Changhe Yuan, Tsai-Ching Lu, Marek J. Druzdzel:
Annealed MAP. CoRR abs/1207.4153 (2012) - [i3]Denver Dash, Marek J. Druzdzel:
A Robust Independence Test for Constraint-Based Learning of Causal Structure. CoRR abs/1212.2464 (2012) - [i2]Changhe Yuan, Marek J. Druzdzel:
An Importance Sampling Algorithm Based on Evidence Pre-propagation. CoRR abs/1212.2507 (2012) - 2011
- [i1]Jian Cheng, Marek J. Druzdzel:
AIS-BN: An Adaptive Importance Sampling Algorithm for Evidential Reasoning in Large Bayesian Networks. CoRR abs/1106.0253 (2011) - 2010
- [c48]Mark Voortman, Denver Dash, Marek J. Druzdzel:
Learning Why Things Change: The Difference-Based Causality Learner. UAI 2010: 641-650 - [c47]Mark Voortman, Denver Dash, Marek J. Druzdzel:
Learning Causal Models That Make Correct Manipulation Predictions. NIPS Causality: Objectives and Assessment 2010: 257-266
2000 – 2009
- 2009
- [j12]Tsai-Ching Lu, Marek J. Druzdzel
Interactive construction of graphical decision models based on causal mechanisms. Eur. J. Oper. Res. 199(3): 873-882 (2009) - [c46]John Mark Agosta, Russell G. Almond, Dennis M. Buede, Marek J. Druzdzel, Judy Goldsmith, Silja Renooij
Workshop summary: Seventh annual workshop on Bayes applications. ICML 2009: 3 - [c45]Marek J. Druzdzel:
Rapid modeling and analysis with QGENIE. IMCSIT 2009: 157-164 - [c44]Parot Ratnapinda
Passive construction of diagnostic decision models: An empirical evaluation. IMCSIT 2009: 601-607 - 2008
- [j11]Denver Dash, Marek J. Druzdzel
A note on the correctness of the causal ordering algorithm. Artif. Intell. 172(15): 1800-1808 (2008) - [c43]Mark Voortman, Marek J. Druzdzel:
Insensitivity of Constraint-Based Causal Discovery Algorithms to Violations of the Assumption of Multivariate Normality. FLAIRS 2008: 690-695 - [c42]Marek J. Druzdzel, Agnieszka Onisko:
The impact of overconfidence bias on practical accuracy of Bayesian network models: an empirical study. BMA 2008 - 2007
- [j10]Changhe Yuan, Marek J. Druzdzel
Theoretical analysis and practical insights on importance sampling in Bayesian networks. Int. J. Approx. Reason. 46(2): 320-333 (2007) - [c41]Changhe Yuan, Marek J. Druzdzel:
Generalized Evidence Pre-propagated Importance Sampling for Hybrid Bayesian Networks. AAAI 2007: 1296-1303 - [c40]Changhe Yuan, Marek J. Druzdzel:
Improving Importance Sampling by Adaptive Split-Rejection Control in Bayesian Networks. Canadian AI 2007: 332-343 - [c39]Martinus de Jongh, Marek J. Druzdzel, Léon J. M. Rothkrantz:
Implementing and improving a method for non-invasive elicitation of probabilities for Bayesian networks. CompSysTech 2007: 117 - [c38]Xiaoxun Sun, Marek J. Druzdzel, Changhe Yuan:
Dynamic Weighting A* Search-Based MAP Algorithm for Bayesian Networks. IJCAI 2007: 2385-2390 - [c37]Changhe Yuan, Marek J. Druzdzel:
Importance Sampling for General Hybrid Bayesian Networks. AISTATS 2007: 652-659 - 2006
- [j9]Changhe Yuan, Marek J. Druzdzel
Importance sampling algorithms for Bayesian networks: Principles and performance. Math. Comput. Model. 43(9-10): 1189-1207 (2006) - [c36]Adam Zagorecki, Marek J. Druzdzel:
Knowledge Engineering for Bayesian Networks: How Common Are Noisy-MAX Distributions in Practice? ECAI 2006: 482- - [c35]Adam Zagorecki, Mark Voortman, Marek J. Druzdzel:
Decomposing Local Probability Distributions in Bayesian Networks for Improved Inference and Parameter Learning. FLAIRS 2006: 860-865 - [c34]Xiaoxun Sun, Marek J. Druzdzel, Changhe Yuan:
Dynamic Weighting A* Search-based MAP Algorithm for Bayesian Networks. Probabilistic Graphical Models 2006: 279-286 - [c33]Changhe Yuan, Marek J. Druzdzel:
Hybrid Loopy Belief Propagation. Probabilistic Graphical Models 2006: 317-324 - [c32]Adam Zagorecki, Marek J. Druzdzel:
Probabilistic Independence of Causal Influences. Probabilistic Graphical Models 2006: 325-332 - 2005
- [j8]Michael L. Anderson, Thomas Barkowsky, Pauline Berry, Douglas S. Blank, Timothy Chklovski, Pedro M. Domingos, Marek J. Druzdzel, Christian Freksa, John Gersh, Mary Hegarty, Tze-Yun Leong, Henry Lieberman, Ric K. Lowe, Susann LuperFoy, Rada Mihalcea, Lisa Meeden, David P. Miller, Tim Oates, Robert L. Popp, Daniel G. Shapiro, Nathan Schurr, Push Singh, John Yen:
Reports on the 2005 AAAI Spring Symposium Series. AI Mag. 26(2): 87-92 (2005) - [c31]Marek J. Druzdzel, Tze-Yun Leong:
Organizing Committee. AAAI Spring Symposium: Challenges to Decision Support in a Changing World 2005 - [c30]Marek J. Druzdzel, Tze-Yun Leong:
Preface. AAAI Spring Symposium: Challenges to Decision Support in a Changing World 2005 - [c29]Tsai-Ching Lu, Marek J. Druzdzel:
Mechanism-based Causal Models for Adaptive Decision Support. AAAI Spring Symposium: Challenges to Decision Support in a Changing World 2005: 73-79 - [c28]Changhe Yuan, Marek J. Druzdzel:
How Heavy Should the Tails Be? FLAIRS 2005: 799-805 - 2004
- [c27]Adam Zagorecki, Marek J. Druzdzel:
An Empirical Study of Probability Elicitation Under Noisy-OR Assumption. FLAIRS 2004: 880-886 - [c26]Changhe Yuan, Tsai-Ching Lu, Marek J. Druzdzel:
Annealed MAP. UAI 2004: 628-635 - 2003
- [j7]Marek J. Druzdzel, Francisco Javier Díez:
Combining Knowledge from Different Sources in Causal Probabilistic Models. J. Mach. Learn. Res. 4: 295-316 (2003) - [c25]Denver Dash, Marek J. Druzdzel:
Robust Independence Testing for Constraint-Based Learning of Causal Structure. UAI 2003: 167-174 - [c24]Changhe Yuan, Marek J. Druzdzel:
An Importance Sampling Algorithm Based on Evidence Pre-propagation. UAI 2003: 624-631 - 2002
- [j6]Haiqin Wang, Denver Dash, Marek J. Druzdzel
A method for evaluating elicitation schemes for probabilistic models. IEEE Trans. Syst. Man Cybern. Part B 32(1): 38-43 (2002) - [c23]Agnieszka Onisko, Marek J. Druzdzel, Hanna Wasyluk:
An Experimental Comparison of Methods for Handling Incomplete Data in Learning Parameters of Bayesian Networks. Intelligent Information Systems 2002: 351-360 - [c22]Tsai-Ching Lu, Marek J. Druzdzel:
Causal Models, Value of Intervention, and Search for Opportunities. Probabilistic Graphical Models 2002 - 2001
- [j5]Agnieszka Onisko, Marek J. Druzdzel
Learning Bayesian network parameters from small data sets: application of Noisy-OR gates. Int. J. Approx. Reason. 27(2): 165-182 (2001) - [j4]Marek J. Druzdzel
Causal reversibility in Bayesian networks. J. Exp. Theor. Artif. Intell. 13(1): 45-62 (2001) - [c21]Agnieszka Onisko, Peter J. F. Lucas, Marek J. Druzdzel:
Comparison of Rule-Based and Bayesian Network Approaches in Medical Diagnostic Systems. AIME 2001: 283-292 - [c20]Denver Dash, Marek J. Druzdzel:
Caveats for Causal Reasoning with Equilibrium Models. ECSQARU 2001: 192-203 - [c19]Tsai-Ching Lu, Marek J. Druzdzel:
Supporting Changes in Structure in Causal Model Construction. ECSQARU 2001: 204-215 - [c18]Haiqin Wang, Denver Dash, Marek J. Druzdzel:
A Method for Evaluating Elicitation Schemes for Probabilities. FLAIRS 2001: 607-612 - [c17]Jian Cheng, Marek J. Druzdzel:
Confidence Inference in Bayesian Networks. UAI 2001: 75-82 - 2000
- [j3]Jian Cheng, Marek J. Druzdzel:
AIS-BN: An Adaptive Importance Sampling Algorithm for Evidential Reasoning in Large Bayesian Networks. J. Artif. Intell. Res. 13: 155-188 (2000) - [c16]Jian Cheng, Marek J. Druzdzel:
Latin Hypercube Sampling in Bayesian Networks. FLAIRS 2000: 287-292 - [c15]Jian Cheng, Marek J. Druzdzel:
Computational Investigation of Low-Discrepancy Sequences in Simulation Algorithms for Bayesian Networks. UAI 2000: 72-81 - [c14]Tsai-Ching Lu, Marek J. Druzdzel, Tze-Yun Leong:
Causal Mechanism-based Model Constructions. UAI 2000: 353-362 - [c13]Haiqin Wang, Marek J. Druzdzel:
User Interface Tools for Navigation in Conditional Probability Tables and Elicitation of Probabilities in Bayesian Networks. UAI 2000: 617-625 - [e1]Marek J. Druzdzel
Building Probabilistic Networks: "Where Do the Numbers Come From?" Guest Editors Introduction. IEEE Trans. Knowl. Data Eng. 12(4): 481-486 (2000)
1990 – 1999
- 1999
- [j2]Yan Lin, Marek J. Druzdzel
Relevance-Based Incremental Belief Updating in Bayesian Networks. Int. J. Pattern Recognit. Artif. Intell. 13(2): 285-295 (1999) - [c12]Marek J. Druzdzel:
SMILE: Structural Modeling, Inference, and Learning Engine and GeNIE: A Development Environment for Graphical Decision-Theoretic Models. AAAI/IAAI 1999: 902-903 - [c11]Marek J. Druzdzel:
GeNIe: A Development Environment for Graphical Decision-Analytic Models. AMIA 1999 - [c10]Marek J. Druzdzel, Agnieszka Onisko, Daniel Schwartz, John N. Dowling, Hanna Wasyluk:
Knowledge Engineering for Very Large Decision-analytic Medical Models. AMIA 1999 - [c9]Denver Dash, Marek J. Druzdzel:
A Hybrid Anytime Algorithm for the Construction of Causal Models From Sparse Data. UAI 1999: 142-149 - 1998
- [c8]Yan Lin, Marek J. Druzdzel:
Relevance-Based Sequential Evidence Processing in Bayesian Networks. FLAIRS 1998: 446-450 - 1997
- [j1]Marek J. Druzdzel:
Five Useful Properties of Probabilistic Knowledge Representations From the Point of View of Intelligent Systems. Fundam. Informaticae 30(3/4): 241-254 (1997) - [c7]Yan Lin, Marek J. Druzdzel:
Computational Advantages of Relevance Reasoning in Bayesian Belief Networks. UAI 1997: 342-350 - 1995
- [c6]Marek J. Druzdzel, Linda C. van der Gaag:
Elicitation of Probabilities for Belief Networks: Combining Qualitative and Quantitative Information. UAI 1995: 141-148 - 1994
- [c5]Marek J. Druzdzel:
Some Properties of joint Probability Distributions. UAI 1994: 187-194 - 1993
- [c4]Marek J. Druzdzel, Max Henrion:
Efficient Reasoning in Qualitative Probabilistic Networks. AAAI 1993: 548-553 - [c3]Marek J. Druzdzel, Herbert A. Simon:
Causality in Bayesian Belief Networks. UAI 1993: 3-11 - [c2]Marek J. Druzdzel, Max Henrion:
Intercausal Reasoning with Uninstantiated Ancestor Nodes. UAI 1993: 317-325 - 1990
- [c1]Max Henrion, Marek J. Druzdzel:
Qualtitative propagation and scenario-based scheme for exploiting probabilistic reasoning. UAI 1990: 17-32
Coauthor Index
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