Emily B. Fox

ORCID

Publication Activity (10 Years)

Years Active: 2006-2024
Publications (10 Years): 37

Top Venues

CoRR

ICML

NIPS

SIAM J. Math. Data Sci.

Massachusetts Institute of Technology, Cambridge, MA, USA (PHD)

Education History

Massachusetts Institute of Technology, Cambridge, MA, USA

PHD

Publications

Michael Y. Li, Emily B. Fox, Noah D. Goodman
Automated Statistical Model Discovery with Language Models. CoRR (2024)
Bob Junyi Zou, Matthew E. Levine, Dessi P. Zaharieva, Ramesh Johari, Emily B. Fox
Hybrid Square Neural ODE Causal Modeling. CoRR (2024)
Ke Alexander Wang, Emily B. Fox
Interpretable Mechanistic Representations for Meal-level Glycemic Control in the Wild. CoRR (2023)
Jiaxin Shi, Ke Alexander Wang, Emily B. Fox
Sequence Modeling with Multiresolution Convolutional Memory. CoRR (2023)
Jiaxin Shi, Ke Alexander Wang, Emily B. Fox
Sequence Modeling with Multiresolution Convolutional Memory. ICML (2023)
Ke Alexander Wang, Emily B. Fox
Interpretable Mechanistic Representations for Meal-level Glycemic Control in the Wild. ML4H@NeurIPS (2023)
Ke Alexander Wang, Matthew E. Levine, Jiaxin Shi, Emily B. Fox
Learning Absorption Rates in Glucose-Insulin Dynamics from Meal Covariates. CoRR (2023)
Alex Tank, Ian Covert, Nicholas J. Foti, Ali Shojaie, Emily B. Fox
Neural Granger Causality. IEEE Trans. Pattern Anal. Mach. Intell. 44 (8) (2022)
Andrew C. Miller, Leon A. Gatys, Joseph Futoma, Emily B. Fox
Model-based metrics: Sample-efficient estimates of predictive model subpopulation performance. MLHC (2021)
Alex Tank, Xiudi Li, Emily B. Fox, Ali Shojaie
The Convex Mixture Distribution: Granger Causality for Categorical Time Series. SIAM J. Math. Data Sci. 3 (1) (2021)
Sean Jewell, Joseph Futoma, Lauren Hannah, Andrew C. Miller, Nicholas J. Foti, Emily B. Fox
It's complicated: characterizing the time-varying relationship between cell phone mobility and COVID-19 spread in the US. npj Digit. Medicine 4 (2021)
Andrew C. Miller, Nicholas J. Foti, Emily B. Fox
Breiman's two cultures: You don't have to choose sides. CoRR (2021)
Ali Shojaie, Emily B. Fox
Granger Causality: A Review and Recent Advances. CoRR (2021)
Joelle Pineau, Philippe Vincent-Lamarre, Koustuv Sinha, Vincent Larivière, Alina Beygelzimer, Florence d'Alché-Buc, Emily B. Fox, Hugo Larochelle
Improving Reproducibility in Machine Learning Research(A Report from the NeurIPS 2019 Reproducibility Program). J. Mach. Learn. Res. 22 (2021)
Andrew C. Miller, Leon A. Gatys, Joseph Futoma, Emily B. Fox
Model-based metrics: Sample-efficient estimates of predictive model subpopulation performance. CoRR (2021)
Joelle Pineau, Philippe Vincent-Lamarre, Koustuv Sinha, Vincent Larivière, Alina Beygelzimer, Florence d'Alché-Buc, Emily B. Fox, Hugo Larochelle
Improving Reproducibility in Machine Learning Research (A Report from the NeurIPS 2019 Reproducibility Program). CoRR (2020)
Andrew C. Miller, Nicholas J. Foti, Emily B. Fox
Learning Insulin-Glucose Dynamics in the Wild. CoRR (2020)
Jeffrey Chan, Andrew C. Miller, Emily B. Fox
Representing and Denoising Wearable ECG Recordings. CoRR (2020)
Andrew C. Miller, Nicholas J. Foti, Emily B. Fox
Learning Insulin-Glucose Dynamics in the Wild. MLHC (2020)
Christopher Aicher, Yi-An Ma, Nicholas J. Foti, Emily B. Fox
Stochastic Gradient MCMC for State Space Models. SIAM J. Math. Data Sci. 1 (3) (2019)
Christopher Aicher, Nicholas J. Foti, Emily B. Fox
Adaptively Truncating Backpropagation Through Time to Control Gradient Bias. UAI (2019)
Jack Baker, Paul Fearnhead, Emily B. Fox, Christopher Nemeth
Control variates for stochastic gradient MCMC. Stat. Comput. 29 (3) (2019)
Yi-An Ma, Emily B. Fox, Tianqi Chen, Lei Wu
Irreversible samplers from jump and continuous Markov processes. Stat. Comput. 29 (1) (2019)
Christopher Xie, Emily B. Fox, Zaïd Harchaoui
A Simple Adaptive Tracker with Reminiscences. ICRA (2019)
Christopher Aicher, Srshti Putcha, Christopher Nemeth, Paul Fearnhead, Emily B. Fox
Stochastic Gradient MCMC for Nonlinear State Space Models. CoRR (2019)
Jonas Rauber, Emily B. Fox, Leon A. Gatys
Modeling patterns of smartphone usage and their relationship to cognitive health. CoRR (2019)
Christopher Aicher, Nicholas J. Foti, Emily B. Fox
Adaptively Truncating Backpropagation Through Time to Control Gradient Bias. CoRR (2019)
Samuel K. Ainsworth, Nicholas J. Foti, Adrian K. C. Lee, Emily B. Fox
oi-VAE: Output Interpretable VAEs for Nonlinear Group Factor Analysis. ICML (2018)
Christopher Aicher, Emily B. Fox
Approximate Collapsed Gibbs Clustering with Expectation Propagation. CoRR (2018)
Samuel K. Ainsworth, Nicholas J. Foti, Adrian K. C. Lee, Emily B. Fox
Interpretable VAEs for nonlinear group factor analysis. CoRR (2018)
Jack Baker, Paul Fearnhead, Emily B. Fox, Christopher Nemeth
Large-Scale Stochastic Sampling from the Probability Simplex. CoRR (2018)
Christopher Aicher, Yi-An Ma, Nicholas J. Foti, Emily B. Fox
Stochastic Gradient MCMC for State Space Models. CoRR (2018)
Samuel K. Ainsworth, Nicholas J. Foti, Emily B. Fox
Disentangled VAE Representations for Multi-Aspect and Missing Data. CoRR (2018)
Jack Baker, Paul Fearnhead, Emily B. Fox, Christopher Nemeth
Large-Scale Stochastic Sampling from the Probability Simplex. NeurIPS (2018)
Yi-An Ma, Nicholas J. Foti, Emily B. Fox
Stochastic Gradient MCMC Methods for Hidden Markov Models. ICML (2017)
Christopher Xie, Alex Tank, Alec Greaves-Tunnell, Emily B. Fox
A Unified Framework for Long Range and Cold Start Forecasting of Seasonal Profiles in Time Series. CoRR (2017)
Jack Baker, Paul Fearnhead, Emily B. Fox, Christopher Nemeth
Control Variates for Stochastic Gradient MCMC. CoRR (2017)
Yi-An Ma, Tianqi Chen, Emily B. Fox
A Complete Recipe for Stochastic Gradient MCMC. NIPS (2015)
Ryan P. Adams, Emily B. Fox, Erik B. Sudderth, Yee Whye Teh
Guest Editors' Introduction to the Special Issue on Bayesian Nonparametrics. IEEE Trans. Pattern Anal. Mach. Intell. 37 (2) (2015)
Emily B. Fox, David B. Dunson
Bayesian nonparametric covariance regression. J. Mach. Learn. Res. 16 (2015)
Alex Tank, Nicholas J. Foti, Emily B. Fox
Streaming Variational Inference for Bayesian Nonparametric Mixture Models. AISTATS (2015)
Alex Tank, Nicholas J. Foti, Emily B. Fox
Bayesian Structure Learning for Stationary Time Series. UAI (2015)
Jennifer Gillenwater, Alex Kulesza, Emily B. Fox, Benjamin Taskar
Expectation-Maximization for Learning Determinantal Point Processes. NIPS (2014)
Tianqi Chen, Emily B. Fox, Carlos Guestrin
Stochastic Gradient Hamiltonian Monte Carlo. ICML (2014)
Nicholas J. Foti, Jason Xu, Dillon Laird, Emily B. Fox
Stochastic variational inference for hidden Markov models. NIPS (2014)
Raja Hafiz Affandi, Emily B. Fox, Ryan P. Adams, Ben Taskar
Learning the Parameters of Determinantal Point Process Kernels. CoRR (2014)
Tianqi Chen, Emily B. Fox, Carlos Guestrin
Stochastic Gradient Hamiltonian Monte Carlo. CoRR (2014)
Raja Hafiz Affandi, Emily B. Fox, Ryan P. Adams, Benjamin Taskar
Learning the Parameters of Determinantal Point Process Kernels. ICML (2014)
Drausin F. Wulsin, Emily B. Fox, Brian Litt
Modeling the complex dynamics and changing correlations of epileptic events. Artif. Intell. 216 (2014)
Francois Caron, Emily B. Fox
Bayesian nonparametric models of sparse and exchangeable random graphs. CoRR (2014)
Jennifer Gillenwater, Alex Kulesza, Emily B. Fox, Ben Taskar
Expectation-Maximization for Learning Determinantal Point Processes. CoRR (2014)
Khalid El-Arini, Min Xu, Emily B. Fox, Carlos Guestrin
Representing documents through their readers. KDD (2013)
Raja Hafiz Affandi, Emily B. Fox, Ben Taskar
Approximate Inference in Continuous Determinantal Processes. NIPS (2013)
Raja Hafiz Affandi, Emily B. Fox, Ben Taskar
Approximate Inference in Continuous Determinantal Point Processes. CoRR (2013)
Tauhid Zaman, Emily B. Fox, Eric T. Bradlow
A Bayesian Approach for Predicting the Popularity of Tweets CoRR (2013)
Emily B. Fox, Michael I. Jordan
Mixed Membership Models for Time Series. CoRR (2013)
Raja Hafiz Affandi, Alex Kulesza, Emily B. Fox, Ben Taskar
Nystrom Approximation for Large-Scale Determinantal Processes. AISTATS (2013)
Drausin Wulsin, Emily B. Fox, Brian Litt
Parsing epileptic events using a Markov switching process model for correlated time series. ICML (1) (2013)
Raja Hafiz Affandi, Alex Kulesza, Emily B. Fox
Markov Determinantal Point Processes. UAI (2012)
Michael C. Hughes, Emily B. Fox, Erik B. Sudderth
Effective Split-Merge Monte Carlo Methods for Nonparametric Models of Sequential Data. NIPS (2012)
Khalid El-Arini, Emily B. Fox, Carlos Guestrin
Concept Modeling with Superwords CoRR (2012)
Emily B. Fox, David B. Dunson
Multiresolution Gaussian Processes. NIPS (2012)
Raja Hafiz Affandi, Alex Kulesza, Emily B. Fox
Markov Determinantal Point Processes CoRR (2012)
Alona Fyshe, Emily B. Fox, David B. Dunson, Tom M. Mitchell
Hierarchical Latent Dictionaries for Models of Brain Activation. AISTATS (2012)
Emily B. Fox, Erik B. Sudderth, Michael I. Jordan, Alan S. Willsky
Bayesian Nonparametric Inference of Switching Dynamic Linear Models. IEEE Trans. Signal Process. 59 (4) (2011)
Emily B. Fox, Erik B. Sudderth, Michael I. Jordan, Alan S. Willsky
Bayesian Nonparametric Methods for Learning Markov Switching Processes. IEEE Signal Process. Mag. 27 (6) (2010)
Emily B. Fox, Erik B. Sudderth, Michael I. Jordan, Alan S. Willsky
Sharing Features among Dynamical Systems with Beta Processes. NIPS (2009)
Emily B. Fox, Erik B. Sudderth, Michael I. Jordan, Alan S. Willsky
An HDP-HMM for systems with state persistence. ICML (2008)
Emily B. Fox, Erik B. Sudderth, Michael I. Jordan, Alan S. Willsky
Nonparametric Bayesian Learning of Switching Linear Dynamical Systems. NIPS (2008)
Emily B. Fox, John W. Fisher III, Alan S. Willsky
Detection and Localization of Material Releases With Sparse Sensor Configurations. IEEE Trans. Signal Process. 55 (5-1) (2007)
Emily B. Fox, Erik B. Sudderth, Alan S. Willsky
Hierarchical Dirichlet processes for tracking maneuvering targets. FUSION (2007)
Emily B. Fox, Jason L. Williams, John W. Fisher III, Alan S. Willsky
Detection and Localization of Material Releases with Sparse Sensor Configurations. ICASSP (4) (2006)

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Publication Activity (10 Years)

Top Topics

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Emily B. Fox