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∙ 12/06/2021

Simulation Intelligence: Towards a New Generation of Scientific Methods

The original "Seven Motifs" set forth a roadmap of essential methods for...

50 Alexander Lavin, et al. ∙

∙ 10/05/2021

Unifying AI Algorithms with Probabilistic Programming using Implicitly Defined Representations

We introduce Scruff, a new framework for developing AI systems using pro...

0 Avi Pfeffer, et al. ∙

∙ 05/15/2017

Learning Probabilistic Programs Using Backpropagation

Probabilistic modeling enables combining domain knowledge with learning ...

0 Avi Pfeffer, et al. ∙

∙ 04/27/2017

Artificial Intelligence Based Malware Analysis

Artificial intelligence methods have often been applied to perform speci...

0 Avi Pfeffer, et al. ∙

∙ 06/10/2016

Structured Factored Inference: A Framework for Automated Reasoning in Probabilistic Programming Languages

Reasoning on large and complex real-world models is a computationally di...

0 Avi Pfeffer, et al. ∙

∙ 09/11/2015

Lazy Factored Inference for Functional Probabilistic Programming

Probabilistic programming provides the means to represent and reason abo...

0 Avi Pfeffer, et al. ∙

∙ 07/11/2014

Decision-Making with Complex Data Structures using Probabilistic Programming

Existing decision-theoretic reasoning frameworks such as decision networ...

0 Brian E. Ruttenberg, et al. ∙

∙ 01/15/2014

Networks of Influence Diagrams: A Formalism for Representing Agents' Beliefs and Decision-Making Processes

This paper presents Networks of Influence Diagrams (NID), a compact, nat...

0 Yaakov Gal, et al. ∙

∙ 02/06/2013

Object-Oriented Bayesian Networks

Bayesian networks provide a modeling language and associated inference a...

0 Daphne Koller, et al. ∙

∙ 01/23/2013

SPOOK: A System for Probabilistic Object-Oriented Knowledge Representation

In previous work, we pointed out the limitations of standard Bayesian ne...

0 Avi Pfeffer, et al. ∙

∙ 01/10/2013

Sufficiency, Separability and Temporal Probabilistic Models

Suppose we are given the conditional probability of one variable given s...

0 Avi Pfeffer, et al. ∙

∙ 12/12/2012

Factored Particles for Scalable Monitoring

Exact monitoring in dynamic Bayesian networks is intractable, so approxi...

0 Brenda Ng, et al. ∙

∙ 10/19/2012

Loopy Belief Propagation as a Basis for Communication in Sensor Networks

Sensor networks are an exciting new kind of computer system. Consisting ...

0 Christopher Crick, et al. ∙

∙ 07/04/2012

Asynchronous Dynamic Bayesian Networks

Systems such as sensor networks and teams of autonomous robots consist o...

0 Avi Pfeffer, et al. ∙

∙ 06/27/2012

Approximate Separability for Weak Interaction in Dynamic Systems

One approach to monitoring a dynamic system relies on decomposition of t...

0 Avi Pfeffer, et al. ∙

∙ 06/13/2012

Learning and Solving Many-Player Games through a Cluster-Based Representation

In addressing the challenge of exponential scaling with the number of ag...

0 Sevan G. Ficici, et al. ∙

∙ 06/13/2012

Identifying reasoning patterns in games

We present an algorithm that identifies the reasoning patterns of agents...

0 Dimitrios Antos, et al. ∙

∙ 05/11/2012

Proceedings of the Twenty-Seventh Conference on Uncertainty in Artificial Intelligence (2011)

This is the Proceedings of the Twenty-Seventh Conference on Uncertainty ...

0 Fabio Cozman, et al. ∙

∙ 05/09/2012

Temporal Action-Graph Games: A New Representation for Dynamic Games

In this paper we introduce temporal action graph games (TAGGs), a novel ...

0 Albert Xin Jiang, et al. ∙

∙ 03/15/2012

Learning Game Representations from Data Using Rationality Constraints

While game theory is widely used to model strategic interactions, a natu...

0 Xi Alice Gao, et al. ∙

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