Matthew D. Hoffman
10 papers · 2013–2023 · 5 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· Half π Interdisciplinary Bridge Β· Bronze πΊοΈ Taxonomy Completionist (17)
π₯
Mega-Team Β· Squad
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Keyword Champion
(2)
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Century Club Β· Bronze
Top co-authors
Research topics
Machine Learning
(9)
Optimization & Theory
(8)
Deep Learning
(5)
Models
(5)
Artificial Intelligence
(3)
Bayesian & Probabilistic Β· Artificial Intelligence
(3)
Bayesian & Probabilistic Β· Machine Learning
(3)
Mathematics & Optimization
(2)
Computer Vision
(1)
Analysis
(1)
Application Areas
(1)
Architectures
(1)
Core Methods
(1)
Optimization
(1)
Probability
(1)
Keywords
markov chain monte carlo
(4)
bayesian inference
(3)
hamiltonian monte carlo
(3)
variational inference
(2)
variational expectation-maximization
(2)
bayesian nonparametrics
(2)
variational autoencoder
(2)
gradient-based sampling
(2)
probabilistic programming
(1)
posterior inference
(1)
latent dirichlet allocation
(1)
distribution shift
(1)
probabilistic topic model
(1)
posterior distribution
(1)
hierarchical clustering
(1)
conditional distribution
(1)
stochastic variational inference
(1)
generative model
(1)
uncertainty quantification
(1)
domain generalization
(1)
Papers
ProbNeRF: Uncertainty-Aware Inference of 3D Shapes from 2D Images
AISTATS 2023
Tuning-Free Generalized Hamiltonian Monte Carlo
AISTATS 2022
Underspecification Presents Challenges for Credibility in Modern Machine Learning
JMLR 2022
Music Transformer: Generating Music with Long-Term Structure
ICLR 2019
The LORACs Prior for VAEs: Letting the Trees Speak for the Data
AISTATS 2019
Autoconj: Recognizing and Exploiting Conjugacy Without a Domain-Specific Language
NeurIPS 2018
Learning Deep Latent Gaussian Models with Markov Chain Monte Carlo
ICML 2017
Stochastic Gradient Descent as Approximate Bayesian Inference
JMLR 2017
The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo
JMLR 2014
Stochastic Variational Inference
JMLR 2013