Andrew Gelman
9 papers · 2014–2024 · 4 venues · across top CS/AI venues
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Achievements
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🌍 Conference Polyglot · Bronze 🏃 Academic Marathon · Half 🌉 Interdisciplinary Bridge · Bronze 🗺️ Taxonomy Completionist (14) 🐣 Hot Topic Early Bird
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The Questioner
Venues
Top co-authors
Research topics
Machine Learning
(9)
Optimization & Theory
(8)
Artificial Intelligence
(5)
Deep Learning
(5)
Models
(5)
Bayesian & Probabilistic · Artificial Intelligence
(4)
Mathematics & Optimization
(2)
Bayesian & Probabilistic · Machine Learning
(2)
Optimization
(2)
Learning Paradigms
(1)
Mathematics
(1)
Probability
(1)
Keywords
variational inference
(7)
markov chain monte carlo
(3)
posterior approximation
(3)
bayesian inference
(3)
hierarchical model
(2)
importance sampling
(2)
probabilistic programming
(2)
hamiltonian monte carlo
(2)
expectation propagation
(2)
automatic differentiation
(2)
distributed computation
(1)
mixture model
(1)
latent variable
(1)
monte carlo method
(1)
multimodal posterior
(1)
importance weight
(1)
pareto distribution
(1)
convergence diagnostic
(1)
goodness of fit
(1)
importance resampling
(1)
Papers
Pareto Smoothed Importance Sampling
JMLR 2024
Federated Learning as Variational Inference: A Scalable Expectation Propagation Approach
ICLR 2023
Pathfinder: Parallel quasi-Newton variational inference
JMLR 2022
Stacking for Non-mixing Bayesian Computations: The Curse and Blessing of Multimodal Posteriors
JMLR 2022
Expectation Propagation as a Way of Life: A Framework for Bayesian Inference on Partitioned Data
JMLR 2020
Yes, but Did It Work?: Evaluating Variational Inference
ICML 2018
Automatic Differentiation Variational Inference
JMLR 2017
Automatic Variational Inference in Stan
NeurIPS 2015
The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo
JMLR 2014