Emily B. Fox
13 papers · 2008–2019 · 4 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
Jump to papers ↓+7 more ↓ Show less ↑
πΊοΈ Taxonomy Completionist (40) π Academic Marathon Β· Half π Conference Polyglot Β· Bronze π Interdisciplinary Bridge Β· Silver π£ Hot Topic Early Bird
π
Keyword Champion
π§
Keyword Pioneer
π
Trend Setter
π
Conference Pioneer
π
Renaissance Researcher
(5)
π
Century Club Β· Bronze
ποΈ
Keyword Collector
(91)
Venues
Top co-authors
Research topics
Machine Learning
(13)
Optimization & Theory
(11)
Bayesian & Probabilistic Β· Machine Learning
(10)
Artificial Intelligence
(8)
Bayesian & Probabilistic Β· Artificial Intelligence
(8)
Learning Types
(6)
Core Methods
(5)
Data Science & Analytics
(4)
Deep Learning
(3)
Methods
(3)
Interdisciplinary
(2)
Mathematics & Optimization
(2)
Optimization
(2)
Science
(2)
Healthcare & Medicine
(1)
Keywords
markov chain monte carlo
(6)
bayesian nonparametrics
(5)
bayesian inference
(5)
time series
(4)
hidden markov model
(3)
variational inference
(3)
stochastic gradient
(2)
stochastic gradient mcmc
(2)
sequential data
(2)
determinantal point process
(2)
time series analysis
(2)
beta process
(2)
latent factor model
(2)
expectation maximization
(1)
gaussian processes
(1)
matrix factorization
(1)
dirichlet process
(1)
gaussian process
(1)
probabilistic modeling
(1)
stochastic gradient descent
(1)
Papers
Adaptively Truncating Backpropagation Through Time to Control Gradient Bias
UAI 2019
Large-Scale Stochastic Sampling from the Probability Simplex
NeurIPS 2018
oi-VAE: Output Interpretable VAEs for Nonlinear Group Factor Analysis
ICML 2018
Stochastic Gradient MCMC Methods for Hidden Markov Models
ICML 2017
A Complete Recipe for Stochastic Gradient MCMC
NeurIPS 2015
Bayesian Nonparametric Covariance Regression
JMLR 2015
Expectation-Maximization for Learning Determinantal Point Processes
NeurIPS 2014
Stochastic variational inference for hidden Markov models
NeurIPS 2014
Approximate Inference in Continuous Determinantal Processes
NeurIPS 2013
Effective Split-Merge Monte Carlo Methods for Nonparametric Models of Sequential Data
NeurIPS 2012
Multiresolution Gaussian Processes
NeurIPS 2012
Sharing Features among Dynamical Systems with Beta Processes
NeurIPS 2009
Nonparametric Bayesian Learning of Switching Linear Dynamical Systems
NeurIPS 2008