publications
2024
2023
- An Explainable Artificial Intelligence Software Tool for Weight Management Experts (PRIMO): Mixed Methods StudyJournal of Medical Internet Research (JMIR) 2023
2022
2020
- Lifted Generalized Belief Propagation: Relax, Compensate & RecoverIn An Introduction to Lifted Probabilistic Inference 2020
- Supervised Learning with Background KnowledgeIn 1st Workshop on Foundations of Trustworthy AI — Integrating Learning, Optimization and Reasoning (TAILOR) 2020
- On Symbolically Encoding the Behavior of Random ForestsIn 3rd Workshop on Formal Methods for ML-Enabled Autonomous Systems (FoMLAS) 2020
2019
- On the Relative Expressiveness of Bayesian and Neural NetworksInternational Journal of Approximate Reasoning (IJAR) 2019
- Conditional Independence in Testing Bayesian NetworksIn Proceedings of the Thirty-Sixth International Conference on Machine Learning (ICML) 2019
- Verifying Binarized Neural Networks by Local Automaton LearningIn AAAI Spring Symposium on Verification of Neural Networks (VNN) 2019
- Compiling Neural Networks into Tractable Boolean CircuitsIn AAAI Spring Symposium on Verification of Neural Networks (VNN) 2019
2018
- Explaining the Decisions of a Route ClassifierIn 13th Women in Machine Learning Workshop (WiML) 2018
2017
2016
- Learning the Structure of Probabilistic SDDsIn 11th Women in Machine Learning Workshop (WiML) 2016
2015
- Learning Bayesian Network Parameters under Equivalence ConstraintsArtificial Intelligence 2015
- Computer Adaptive Testing Using the Same-Decision ProbabilityIn 12th Annual Bayesian Modeling Applications Workshop (BMAW) 2015
- Probability Distributions over Structured SpacesIn AAAI Spring Symposium on Knowledge Representation and Reasoning: Integrating Symbolic and Neural Approaches (KRR) 2015
2014
- Algorithms and Applications for the Same-Decision ProbabilityJournal of Artificial Intelligence Research (JAIR) 2014
- Efficient Algorithms for Bayesian Network Parameter Learning from Incomplete DataIn ICML Workshop on Causal Modeling & Machine Learning 2014
- Probabilistic Sentential Decision Diagrams: Learning with Massive Logical ConstraintsIn ICML Workshop on Learning Tractable Probabilistic Models (LTPM) 2014
2013
- EDML for Learning Parameters in Directed and Undirected Graphical ModelsIn ICML 2013 Workshop on Inferning: Interactions between Inference and Learning 2013
- Learning Bayesian Networks under Equivalence Constraints (Abstract)In Second Workshop on Combining Constraint Solving with Mining and Learning (CoCoMiLe) 2013
2012
2011
2010
- Optimal Algorithms for Haplotype Assembly from Whole-Genome Sequence DataBioinformatics [ISMB] 2010
- Optimal Algorithms for Haplotype Assembly From Whole-Genome Sequence DataIn Proceedings of the 18th Annual International Conference on Intelligent Systems for Molecular Biology (ISMB) 2010
2009
2008
- Efficient Genome Wide Tagging by Reduction to SATIn Proceedings of the 8th Workshop on Algorithms in Bioinformatics (WABI) 2008
- Approximating the Partition Function by Deleting and then Correcting for Model EdgesIn Information Theory and Applications Workshop 2008
2007
- Approximating the Partition Function by Deleting and then Correcting for Model EdgesIn NIPS Workshop on Approximate Bayesian Inference in Continuous/Hybrid Systems 2007
- A New Semantics for Belief Propagation: Theoretical and Practical ImplicationsIn Information Theory and Applications Workshop 2007