Vikash Mansinghka
16 papers · 2005–2026 · 6 venues · across top CS/AI venues
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Achievements
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π£ Hot Topic Early Bird π Conference Polyglot Β· Silver π Academic Marathon Β· Ultra π Interdisciplinary Bridge Β· Bronze πΊοΈ Taxonomy Completionist (19)
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Topic Evolution
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Keyword Collector
(63)
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Century Club Β· Bronze
π₯
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Renaissance Researcher
(5)
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Research topics
Machine Learning
(11)
Optimization & Theory
(10)
Artificial Intelligence
(7)
Bayesian & Probabilistic Β· Artificial Intelligence
(7)
Computer Vision
(2)
Mathematics & Optimization
(2)
Analysis
(2)
Bayesian & Probabilistic Β· Machine Learning
(2)
Core Methods
(2)
Mathematics
(2)
Data Science & Analytics
(1)
Healthcare & Medicine
(1)
Application Areas
(1)
Core AI
(1)
Learning Types
(1)
Keywords
sequential monte carlo
(4)
markov chain monte carlo
(4)
probabilistic programming
(4)
bayesian nonparametrics
(3)
scene understanding
(2)
bayesian inference
(2)
gaussian process
(2)
monte carlo inference
(2)
gibbs sampling
(2)
generative model
(2)
mutual information
(1)
importance sampling
(1)
time series
(1)
time series modeling
(1)
variational inference
(1)
effective sample size
(1)
time series forecasting
(1)
risk-aware planning
(1)
random sampling
(1)
structure learning
(1)
Papers
GenMatter: Perceiving Physical Objects with Generative Matter Models
CVPR 2026
Syntactic and Semantic Control of Large Language Models via Sequential Monte Carlo
ICLR 2025
Partially Observable Task and Motion Planning with Uncertainty and Risk Awareness
RSS 2024
Sequential Monte Carlo Learning for Time Series Structure Discovery
ICML 2023
Estimators of Entropy and Information via Inference in Probabilistic Models
AISTATS 2022
PClean: Bayesian Data Cleaning at Scale with Domain-Specific Probabilistic Programming
AISTATS 2021
Causal Inference using Gaussian Processes with Structured Latent Confounders
ICML 2020
The Fast Loaded Dice Roller: A Near-Optimal Exact Sampler for Discrete Probability Distributions
AISTATS 2020
Temporally-Reweighted Chinese Restaurant Process Mixtures for Clustering, Imputing, and Forecasting Multivariate Time Series
AISTATS 2018
Detecting Dependencies in Sparse, Multivariate Databases Using Probabilistic Programming and Non-parametric Bayes
AISTATS 2017
CrossCat: A Fully Bayesian Nonparametric Method for Analyzing Heterogeneous, High Dimensional Data
JMLR 2016
JUMP-Means: Small-Variance Asymptotics for Markov Jump Processes
ICML 2015
Particle Gibbs with Ancestor Sampling for Probabilistic Programs
AISTATS 2015
Picture: A Probabilistic Programming Language for Scene Perception
CVPR 2015
A New Approach to Probabilistic Programming Inference
AISTATS 2014
Exact and Approximate Sampling by Systematic Stochastic Search
AISTATS 2005