Vikash K. Mansinghka

13 papers · 2006–2023 · 5 conferences · across top CS/AI conferences

Achievements

+10 more ↓

🧭 Keyword Pioneer 🌉 Interdisciplinary Bridge 🌈 Renaissance Researcher (6) 🗺️ Taxonomy Completionist (10) 🌍 Conference Polyglot (5)

🏃 Academic Marathon (17) 🧭 Keyword Pioneer 🌉 Interdisciplinary Bridge 🌟 Keyword Trendsetter Combo (4) 🏆 Keyword Champion 💎 Century Club (13) 📈 Trend Setter 🚀 Conference Pioneer 🔥 Unstoppable (5) 🗃️ Keyword Collector (70)

Conferences

NIPS (6) AISTATS (3) UAI (2) ICCV (1) JMLR (1)

Top co-authors

Vikash K Mansinghka (3) Josh Tenenbaum (3) Marco Cusumano-Towner (3) Nishad Gothoskar (3) Dan Gutfreund (2) Joshua B. Tenenbaum (2) Tan Zhi-Xuan (2) Feras A. Saad (2) Matin Ghavamizadeh (2) Alexander K. Lew (2)

Keywords

markov chain monte carlo (4) probabilistic programming (4) bayesian inference (3) generative model (3) variational inference (3) uncertainty quantification (2) relational datum (2) auxiliary variable (2) sequential monte carlo (2) monte carlo method (2) posterior inference (2) kl divergence (1) bounded rationality (1) probabilistic inference (1) computer vision (1) approximate inference (1) structure learning (1) image interpretation (1) relational learning (1) pose estimation (1)

Papers

3D Neural Embedding Likelihood: Probabilistic Inverse Graphics for Robust 6D Pose Estimation ICCV 2023 SMCP3: Sequential Monte Carlo with Probabilistic Program Proposals AISTATS 2023 ProbNeRF: Uncertainty-Aware Inference of 3D Shapes from 2D Images AISTATS 2023 Recursive Monte Carlo and variational inference with auxiliary variables UAI 2022 3DP3: 3D Scene Perception via Probabilistic Programming NIPS 2021 Hierarchical infinite relational model UAI 2021 Online Bayesian Goal Inference for Boundedly Rational Planning Agents NIPS 2020 A Family of Exact Goodness-of-Fit Tests for High-Dimensional Discrete Distributions AISTATS 2019 AIDE: An algorithm for measuring the accuracy of probabilistic inference algorithms NIPS 2017 Variational Particle Approximations JMLR 2017 A Probabilistic Programming Approach To Probabilistic Data Analysis NIPS 2016 Approximate Bayesian Image Interpretation using Generative Probabilistic Graphics Programs NIPS 2013 Learning annotated hierarchies from relational data NIPS 2006