Vibhav Gogate
Cited by
Cited by
Proving program termination
B Cook, A Podelski, A Rybalchenko
Communications of the ACM 54 (5), 88-98, 2011
Probabilistic theorem proving
V Gogate, P Domingos
arXiv preprint arXiv:1202.3724, 2012
A complete anytime algorithm for treewidth
V Gogate, R Dechter
arXiv preprint arXiv:1207.4109, 2012
SampleSearch: Importance sampling in presence of determinism
V Gogate, R Dechter
Artificial Intelligence 175 (2), 694-729, 2011
Lifted inference seen from the other side: The tractable features
A Jha, V Gogate, A Meliou, D Suciu
Advances in Neural Information Processing Systems 23, 973-981, 2010
Approximate counting by sampling the backtrack-free search space
V Gogate, R Dechter
AAAI, 198-203, 2007
On lifting the gibbs sampling algorithm
D Venugopal, V Gogate
Advances in Neural Information Processing Systems 25, 1655-1663, 2012
Join-graph propagation algorithms
R Mateescu, K Kask, V Gogate, R Dechter
Journal of Artificial Intelligence Research 37, 279-328, 2010
Approximate inference algorithms for hybrid bayesian networks with discrete constraints
V Gogate, R Dechter
arXiv preprint arXiv:1207.1385, 2012
Samplesearch: A scheme that searches for consistent samples
V Gogate, R Dechter
Artificial Intelligence and Statistics, 147-154, 2007
Cutset networks: A simple, tractable, and scalable approach for improving the accuracy of Chow-Liu trees
T Rahman, P Kothalkar, V Gogate
Joint European conference on machine learning and knowledge discovery in …, 2014
A new algorithm for sampling csp solutions uniformly at random
V Gogate, R Dechter
International Conference on Principles and Practice of Constraint …, 2006
Evidence-based clustering for scalable inference in markov logic
D Venugopal, V Gogate
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2014
Relieving the computational bottleneck: Joint inference for event extraction with high-dimensional features
D Venugopal, C Chen, V Gogate, V Ng
Proceedings of the 2014 Conference on Empirical Methods in Natural Language …, 2014
Learning efficient Markov networks
V Gogate, W Webb, P Domingos
Advances in neural information processing systems 23, 748-756, 2010
Counting-based look-ahead schemes for constraint satisfaction
K Kask, R Dechter, V Gogate
International Conference on Principles and Practice of Constraint …, 2004
Lifted MAP inference for Markov logic networks
S Sarkhel, D Venugopal, P Singla, V Gogate
Artificial Intelligence and Statistics, 859-867, 2014
Advances in lifted importance sampling
V Gogate, A Jha, D Venugopal
Proceedings of the AAAI Conference on Artificial Intelligence 26 (1), 2012
Modeling transportation routines using hybrid dynamic mixed networks
V Gogate, R Dechter, B Bidyuk, C Rindt, J Marca
arXiv preprint arXiv:1207.1384, 2012
Merging Strategies for Sum-Product Networks: From Trees to Graphs.
T Rahman, V Gogate
UAI, 2016
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