Vibhav Gogate

1.6k citations
61 papers · 731 indexed · h-index 14
Topics
Bayesian Modeling and Causal Inference (48 papers)Machine Learning and Algorithms (23 papers)Data Management and Algorithms (14 papers)
Journals
SHILAP Revista de lepidopterologíaCommunications of the ACMArtificial Intelligence
Partner nations
United StatesIndia

In The Last Decade

Vibhav Gogate

58 papers receiving 685 citations

Peers

Vibhav Gogate
Comparison fields: 5 of 62
  • Artificial Intelligence 628
  • Signal Processing 124
  • Computer Networks and Communications 110
  • Management Science and Operations Research 84
  • Computational Theory and Mathematics 71
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Citations per field
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Citations per year

Countries citing papers authored by Vibhav Gogate

Since Specialization
Citations

This map shows the geographic impact of Vibhav Gogate's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Vibhav Gogate with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Vibhav Gogate more than expected).

Fields of papers citing papers by Vibhav Gogate

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Vibhav Gogate. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Vibhav Gogate. The network helps show where Vibhav Gogate may publish in the future.

Co-authorship network of co-authors of Vibhav Gogate

This figure shows the co-authorship network connecting the top 25 collaborators of Vibhav Gogate. A scholar is included among the top collaborators of Vibhav Gogate based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Vibhav Gogate. Vibhav Gogate is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1
Explainable Activity Recognition in Videos.
7
2
Dissociation-Based Oblivious Bounds for Weighted Model Counting
1
3
Merging strategies for sum-product networks: from trees to graphs
11
4
Joint Inference for Event Coreference Resolution.
23
5
Fast lifted MAP inference via partitioning
7
6
Scaling-up Importance Sampling for Markov Logic Networks
9
7
Lifting WALKSAT-based local search algorithms for map inference
1
8
The inclusion-exclusion rule and its application to the junction tree algorithm
1
9
On Lifting the Gibbs Sampling Algorithm
31
10
Exploiting logical structure in lifted probabilistic inference
11
11
On Combining Graph-based Variance Reduction schemes
2
12
Learning Efficient Markov Networks
19
13
Lifted Inference Seen from the Other Side : The Tractable Features
37
14
Studies in solution sampling
4
15
Studies in lower bounding probability of evidence using the Markov inequality
10
16
SampleSearch: A Scheme that Searches for Consistent Samples
2
17
Approximate counting by sampling the backtrack-free search space
22
18
Approximate inference in probabilistic graphical models with determinism
0
19 77
20
New Look-Ahead Schemes for Constraint Satisfaction
1

About Vibhav Gogate

Vibhav Gogate is a scholar working on Artificial Intelligence, Signal Processing and Computer Networks and Communications, having authored 61 papers that have together received 731 indexed citations. Recurring topics across this work include Bayesian Modeling and Causal Inference (48 papers), Machine Learning and Algorithms (23 papers) and Data Management and Algorithms (14 papers). The work is most often cited by research in Artificial Intelligence (628 citations), Health Informatics (24 citations) and Signal Processing (124 citations). Vibhav Gogate has collaborated with scholars based in United States and India. Frequent co-authors include Rina Dechter, Pedro Domingos, Deepak Venugopal, Eric D. Ragan, Parag Singla, Chen Chen, Vincent Ng, Abhay K. Jha, Alexandra Meliou and Dan Suciu. Their work appears in journals such as SHILAP Revista de lepidopterología, Communications of the ACM and Artificial Intelligence.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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