
Learning Probabilistic Programs Using Backpropagation
Probabilistic modeling enables combining domain knowledge with learning ...
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Artificial Intelligence Based Malware Analysis
Artificial intelligence methods have often been applied to perform speci...
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Structured Factored Inference: A Framework for Automated Reasoning in Probabilistic Programming Languages
Reasoning on large and complex realworld models is a computationally di...
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Lazy Factored Inference for Functional Probabilistic Programming
Probabilistic programming provides the means to represent and reason abo...
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DecisionMaking with Complex Data Structures using Probabilistic Programming
Existing decisiontheoretic reasoning frameworks such as decision networ...
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Networks of Influence Diagrams: A Formalism for Representing Agents' Beliefs and DecisionMaking Processes
This paper presents Networks of Influence Diagrams (NID), a compact, nat...
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ObjectOriented Bayesian Networks
Bayesian networks provide a modeling language and associated inference a...
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SPOOK: A System for Probabilistic ObjectOriented Knowledge Representation
In previous work, we pointed out the limitations of standard Bayesian ne...
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Sufficiency, Separability and Temporal Probabilistic Models
Suppose we are given the conditional probability of one variable given s...
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Factored Particles for Scalable Monitoring
Exact monitoring in dynamic Bayesian networks is intractable, so approxi...
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Loopy Belief Propagation as a Basis for Communication in Sensor Networks
Sensor networks are an exciting new kind of computer system. Consisting ...
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Asynchronous Dynamic Bayesian Networks
Systems such as sensor networks and teams of autonomous robots consist o...
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Approximate Separability for Weak Interaction in Dynamic Systems
One approach to monitoring a dynamic system relies on decomposition of t...
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Learning and Solving ManyPlayer Games through a ClusterBased Representation
In addressing the challenge of exponential scaling with the number of ag...
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Identifying reasoning patterns in games
We present an algorithm that identifies the reasoning patterns of agents...
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Proceedings of the TwentySeventh Conference on Uncertainty in Artificial Intelligence (2011)
This is the Proceedings of the TwentySeventh Conference on Uncertainty ...
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Temporal ActionGraph Games: A New Representation for Dynamic Games
In this paper we introduce temporal action graph games (TAGGs), a novel ...
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Learning Game Representations from Data Using Rationality Constraints
While game theory is widely used to model strategic interactions, a natu...
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