Vikash K. Mansinghka

2.4k citations
43 papers · 692 indexed · h-index 12
Topics
Bayesian Modeling and Causal Inference (19 papers)Machine Learning and Algorithms (12 papers)Machine Learning and Data Classification (6 papers)

In The Last Decade

Vikash K. Mansinghka

40 papers receiving 637 citations

Peers

Vikash K. Mansinghka
Comparison fields: 5 of 88
  • Artificial Intelligence 390
  • Cognitive Neuroscience 116
  • Developmental and Educational Psychology 108
  • Computer Vision and Pattern Recognition 74
  • Computational Theory and Mathematics 72
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Olivier Sigaud France
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Vikash K. Mansinghka relative to Olivier Sigaud France Olivier Sigaud's profile →
Citations per field
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Citations per year

Countries citing papers authored by Vikash K. Mansinghka

Since Specialization
Citations

This map shows the geographic impact of Vikash K. Mansinghka'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 Vikash K. Mansinghka with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Vikash K. Mansinghka more than expected).

Fields of papers citing papers by Vikash K. Mansinghka

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Vikash K. Mansinghka. 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 Vikash K. Mansinghka. The network helps show where Vikash K. Mansinghka may publish in the future.

Co-authorship network of co-authors of Vikash K. Mansinghka

This figure shows the co-authorship network connecting the top 25 collaborators of Vikash K. Mansinghka. A scholar is included among the top collaborators of Vikash K. Mansinghka 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 Vikash K. Mansinghka. Vikash K. Mansinghka 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 3
2 11
3 1
4 0
5 35
6 6
7
Online Bayesian Goal Inference for Boundedly Rational Planning Agents
1
8
Leveraging Unstructured Statistical Knowledge in a Probabilistic Language of Thought.
1
9 17
10 1
11
A Bayesian Nonparametric Method for Clustering Imputation, and Forecasting in Multivariate Time Series.
1
12
A Probabilistic Programming Approach To Probabilistic Data Analysis
6
13
CrossCat: a fully Bayesian nonparametric method for analyzing heterogeneous, high dimensional data
6
14
Particle Gibbs with Ancestor Sampling for Probabilistic Programs
3
15
JUMP-Means: Small-Variance Asymptotics for Markov Jump Processes
1
16
Exact and approximate sampling by systematic stochastic search
3
17
Learning Grounded Causal Models
11
18
AClass: A simple, online, parallelizable algorithm for probabilistic classification
4
19
Modeling Human Performance on Statistical Word Segmentation Tasks
10
20
Intuitive Theories of Mind: A Rational Approach to False Belief
58

About Vikash K. Mansinghka

Vikash K. Mansinghka is a scholar working on Artificial Intelligence, Signal Processing and Aging, having authored 43 papers that have together received 692 indexed citations. Recurring topics across this work include Bayesian Modeling and Causal Inference (19 papers), Machine Learning and Algorithms (12 papers) and Machine Learning and Data Classification (6 papers). The work is most often cited by research in General Decision Sciences (26 citations), Aging (22 citations) and Artificial Intelligence (390 citations). Vikash K. Mansinghka has collaborated with scholars based in United States, United Kingdom and Denmark. Frequent co-authors include Joshua B. Tenenbaum, Noah D. Goodman, Daniel M. Roy, Keith Bonawitz, Thomas L. Griffiths, Adam N. Sanborn, Tejas D. Kulkarni, Marco Cusumano-Towner, Pushmeet Kohli and Alison Gopnik. Their work appears in journals such as Cell, Psychological Review and Current Biology.

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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