Abstract is missing.
- Deep Transfer as Structure Learning in Markov Logic NetworksDavid Andrew Moore, Andrea Pohoreckyj Danyluk. [doi]
- Exploiting Causal Independence in Markov Logic Networks: Combining Undirected and Directed ModelsSriraam Natarajan, Tushar Khot, Daniel Lowd, Prasad Tadepalli, Kristian Kersting, Jude W. Shavlik. [doi]
- Efficient Lifting for Online Probabilistic InferenceAniruddh Nath, Pedro Domingos. [doi]
- Approximate Lifted Belief PropagationParag Singla, Aniruddh Nath, Pedro Domingos. [doi]
- Automatic Inference in BLOGNimar S. Arora, Stuart J. Russell, Erik B. Sudderth. [doi]
- Using Structural Motifs for Learning Markov Logic NetworksStanley Kok, Pedro Domingos. [doi]
- Stochastic Planning and Lifted InferenceRoni Khardon. [doi]
- Lifted Message Passing for SatisfiabilityFabian Hadiji, Kristian Kersting, Babak Ahmadi. [doi]
- Probabilistic Programming for Planning ProblemsIngo Thon, Bernd Gutmann, Guy Van den Broeck. [doi]
- Integrating Structured Metadata with Relational Affinity PropagationAnon Plangprasopchok, Kristina Lerman, Lise Getoor. [doi]
- Machine Reading: A "Killer App" for Statistical Relational AIHoifung Poon, Pedro Domingos. [doi]
- Lifted Inference for Relational Continuous ModelsJaesik Choi, David J. Hill, Eyal Amir. [doi]
- Declarative Probabilistic Programming for Undirected Graphical Models: Open Up to Scale UpSebastian Robert Riedel. [doi]
- An Architectural Approach to Statistical Relational AIPaul S. Rosenbloom. [doi]
- Online Max-Margin Weight Learning with Markov Logic NetworksTuyen N. Huynh, Raymond J. Mooney. [doi]
- Exploiting Logical Structure in Lifted Probabilistic InferenceVibhav Gogate, Pedro Domingos. [doi]
- Relational Learning for Collective Classification of Entities in ImagesAnton Chechetka, Denver Dash, Matthai Philipose. [doi]
- Leveraging Ontologies for Lifted Probabilistic Inference and LearningChloe Kiddon, Pedro Domingos. [doi]
- Bayesian Abductive Logic ProgramsSindhu Raghavan, Raymond J. Mooney. [doi]