Gogate, Vibhav - Department of Computer Science, University of Texas at Dallas

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Gogate, Vibhav - Department of Computer Science, University of Texas at Dallas

A New Algorithm for Sampling CSP Solutions Uniformly at Random
Approximate Inference in Probabilistic Graphical Models with Determinism Vibhav Gogate
Formula-Based Probabilistic Inference Vibhav Gogate and Pedro Domingos
AND/OR Importance Sampling Vibhav Gogate and Rina Dechter
Decision Trees Vibhav Gogate
Journal of Artificial Intelligence Research 37 (2010) 279-328 Submitted 05/09; published 03/10 Join-Graph Propagation Algorithms
SampleSearch: Importance Sampling in presence of Determinism Vibhav Gogate,a
Counting-Based Look-Ahead Schemes for Constraint Satisfaction
A Complete Anytime Algorithm for Treewidth Vibhav Gogate and Rina Dechter
A New Algorithm for Sampling CSP Solutions Uniformly at Random
On Combining Graph-based Variance Reduction schemes Vibhav Gogate Rina Dechter
Modeling Transportation Routines using Hybrid Dynamic Mixed Networks Vibhav Gogate, Rina Dechter, Bozhena Bidyuk
Approximate Counting by Sampling the Backtrack-free Search Space Vibhav Gogate and Rina Dechter
UNIVERSITY OF CALIFORNIA, Sampling Algorithms for Probabilistic Graphical Models with Determinism
Learning Efficient Markov Networks Vibhav Gogate William Austin Webb Pedro Domingos
SampleSearch: A Scheme that Searches for Consistent Samples Vibhav Gogate and Rina Dechter
Sampling Techniques for Probabilistic and Deterministic Graphical models
Approximate Solution Sampling ( and Counting) on AND/OR search space
Approximation by Quantization Vibhav Gogate and Pedro Domingos
Exploiting Logical Structure in Lifted Probabilistic Inference Vibhav Gogate and Pedro Domingos
Sampling-based Lower Bounds for Counting Queries Vibhav Gogate
Lifted Inference Seen from the Other Side : The Tractable Features
New Look-Ahead Schemes for Constraint Satisfaction Kalev Kask, Rina Dechter and Vibhav Gogate
Modeling Travel and Activity Routines using Hybrid Dynamic Mixed Networks Vibhav Gogate
A Simple Application of Sampling Importance Re-sampling (SIR) for Solution Sampling
Probabilistic Theorem Proving Vibhav Gogate and Pedro Domingos
Importance Sampling based Estimation over AND/OR Search Spaces for Graphical Models
Studies in Solution Sampling Vibhav Gogate and Rina Dechter
Studies in Lower Bounding Probability of Evidence using the Markov Vibhav Gogate
Approximate Inference Algorithms for Hybrid Bayesian Networks with Discrete Constraints