Detection and Localization of Material Releases with Sparse Sensor Configurations. - Emily B. Fox; Jason L. Williams; John W. Fisher III; Alan S. Willsky (ICASSP (4), 2006)

Hierarchical Dirichlet processes for tracking maneuvering targets. - Emily B. Fox; Erik B. Sudderth; Alan S. Willsky (FUSION, 2007)

Detection and Localization of Material Releases With Sparse Sensor Configurations. - Emily B. Fox; John W. Fisher III; Alan S. Willsky (IEEE Trans. Signal Process., 2007)

An HDP-HMM for systems with state persistence. - Emily B. Fox; Erik B. Sudderth; Michael I. Jordan; Alan S. Willsky (ICML, 2008)

Nonparametric Bayesian Learning of Switching Linear Dynamical Systems. - Emily B. Fox; Erik B. Sudderth; Michael I. Jordan; Alan S. Willsky (NIPS, 2008)

Sharing Features among Dynamical Systems with Beta Processes. - Emily B. Fox; Erik B. Sudderth; Michael I. Jordan; Alan S. Willsky (NIPS, 2009)

Bayesian nonparametric learning of complex dynamical phenomena. - Emily B. Fox (2009)

Bayesian Nonparametric Methods for Learning Markov Switching Processes. - Emily B. Fox; Erik B. Sudderth; Michael I. Jordan; Alan S. Willsky (IEEE Signal Process. Mag., 2010)

Bayesian Nonparametric Inference of Switching Dynamic Linear Models. - Emily B. Fox; Erik B. Sudderth; Michael I. Jordan; Alan S. Willsky (IEEE Trans. Signal Process., 2011)

Multiresolution Gaussian Processes. - Emily B. Fox; David B. Dunson (NIPS, 2012)

Effective Split-Merge Monte Carlo Methods for Nonparametric Models of Sequential Data. - Michael C. Hughes; Emily B. Fox; Erik B. Sudderth (NIPS, 2012)

Markov Determinantal Point Processes. - Raja Hafiz Affandi; Alex Kulesza; Emily B. Fox (UAI, 2012)

Concept Modeling with Superwords - Khalid El-Arini; Emily B. Fox; Carlos Guestrin (CoRR, 2012)

Hierarchical Latent Dictionaries for Models of Brain Activation. - Alona Fyshe; Emily B. Fox; David B. Dunson; Tom M. Mitchell (AISTATS, 2012)

Nystrom Approximation for Large-Scale Determinantal Processes. - Raja Hafiz Affandi; Alex Kulesza; Emily B. Fox; Ben Taskar (AISTATS, 2013)

Parsing epileptic events using a Markov switching process model for correlated time series. - Drausin Wulsin; Emily B. Fox; Brian Litt (ICML (1), 2013)

Representing documents through their readers. - Khalid El-Arini; Min Xu 010; Emily B. Fox; Carlos Guestrin (KDD, 2013)

Approximate Inference in Continuous Determinantal Processes. - Raja Hafiz Affandi; Emily B. Fox; Ben Taskar (NIPS, 2013)

Approximate Inference in Continuous Determinantal Point Processes. - Raja Hafiz Affandi; Emily B. Fox; Ben Taskar (CoRR, 2013)

Mixed Membership Models for Time Series. - Emily B. Fox; Michael I. Jordan (CoRR, 2013)

A Bayesian Approach for Predicting the Popularity of Tweets - Tauhid Zaman; Emily B. Fox; Eric T. Bradlow (CoRR, 2013)

Learning the Parameters of Determinantal Point Process Kernels. - Raja Hafiz Affandi; Emily B. Fox; Ryan P. Adams; Benjamin Taskar (ICML, 2014)

Stochastic Gradient Hamiltonian Monte Carlo. - Tianqi Chen 001; Emily B. Fox; Carlos Guestrin (ICML, 2014)

Stochastic variational inference for hidden Markov models. - Nicholas J. Foti; Jason Xu; Dillon Laird; Emily B. Fox (NIPS, 2014)

Expectation-Maximization for Learning Determinantal Point Processes. - Jennifer Gillenwater; Alex Kulesza; Emily B. Fox; Benjamin Taskar (NIPS, 2014)

Modeling the complex dynamics and changing correlations of epileptic events. - Drausin F. Wulsin; Emily B. Fox; Brian Litt (Artif. Intell., 2014)

Bayesian nonparametric models of sparse and exchangeable random graphs. - Francois Caron; Emily B. Fox (CoRR, 2014)

Mixed Membership Models for Time Series. - Emily B. Fox; Michael I. Jordan (Handbook of Mixed Membership Models and Their Applications, 2014)

Streaming Variational Inference for Bayesian Nonparametric Mixture Models. - Alex Tank; Nicholas J. Foti; Emily B. Fox (AISTATS, 2015)

A Complete Recipe for Stochastic Gradient MCMC. - Yi-An Ma; Tianqi Chen 001; Emily B. Fox (NIPS, 2015)

Bayesian Structure Learning for Stationary Time Series. - Alex Tank; Nicholas J. Foti; Emily B. Fox (UAI, 2015)

Bayesian nonparametric covariance regression. - Emily B. Fox; David B. Dunson (J. Mach. Learn. Res., 2015)

Guest Editors' Introduction to the Special Issue on Bayesian Nonparametrics. - Ryan P. Adams; Emily B. Fox; Erik B. Sudderth; Yee Whye Teh (IEEE Trans. Pattern Anal. Mach. Intell., 2015)

Stochastic Gradient MCMC Methods for Hidden Markov Models. - Yi-An Ma; Nicholas J. Foti; Emily B. Fox (ICML, 2017)

A Unified Framework for Long Range and Cold Start Forecasting of Seasonal Profiles in Time Series. - Christopher Xie; Alex Tank; Alec Greaves-Tunnell; Emily B. Fox (CoRR, 2017)

oi-VAE: Output Interpretable VAEs for Nonlinear Group Factor Analysis. - Samuel K. Ainsworth; Nicholas J. Foti; Adrian K. C. Lee; Emily B. Fox (ICML, 2018)

Large-Scale Stochastic Sampling from the Probability Simplex. - Jack Baker; Paul Fearnhead; Emily B. Fox; Christopher Nemeth (NeurIPS, 2018)

Interpretable VAEs for nonlinear group factor analysis. - Samuel K. Ainsworth; Nicholas J. Foti; Adrian K. C. Lee; Emily B. Fox (CoRR, 2018)

Disentangled VAE Representations for Multi-Aspect and Missing Data. - Samuel K. Ainsworth; Nicholas J. Foti; Emily B. Fox (CoRR, 2018)

Approximate Collapsed Gibbs Clustering with Expectation Propagation. - Christopher Aicher; Emily B. Fox (CoRR, 2018)

A Simple Adaptive Tracker with Reminiscences. - Christopher Xie; Emily B. Fox; Zaïd Harchaoui (ICRA, 2019)

Adaptively Truncating Backpropagation Through Time to Control Gradient Bias. - Christopher Aicher; Nicholas J. Foti; Emily B. Fox (UAI, 2019)

Stochastic Gradient MCMC for Nonlinear State Space Models. - Christopher Aicher; Srshti Putcha; Christopher Nemeth; Paul Fearnhead; Emily B. Fox (CoRR, 2019)

Modeling patterns of smartphone usage and their relationship to cognitive health. - Jonas Rauber; Emily B. Fox; Leon A. Gatys (CoRR, 2019)

Control variates for stochastic gradient MCMC. - Jack Baker; Paul Fearnhead; Emily B. Fox; Christopher Nemeth (Stat. Comput., 2019)

Irreversible samplers from jump and continuous Markov processes. - Yi-An Ma; Emily B. Fox; Tianqi Chen 001; Lei Wu (Stat. Comput., 2019)

Stochastic Gradient MCMC for State Space Models. - Christopher Aicher; Yi-An Ma; Nicholas J. Foti; Emily B. Fox (SIAM J. Math. Data Sci., 2019)

Learning Insulin-Glucose Dynamics in the Wild. - Andrew C. Miller; Nicholas J. Foti; Emily B. Fox (MLHC, 2020)

Representing and Denoising Wearable ECG Recordings. - Jeffrey Chan; Andrew C. Miller; Emily B. Fox (CoRR, 2020)

Model-based metrics: Sample-efficient estimates of predictive model subpopulation performance. - Andrew C. Miller; Leon A. Gatys; Joseph Futoma; Emily B. Fox (MLHC, 2021)

Breiman's two cultures: You don't have to choose sides. - Andrew C. Miller; Nicholas J. Foti; Emily B. Fox (CoRR, 2021)

Granger Causality: A Review and Recent Advances. - Ali Shojaie; Emily B. Fox (CoRR, 2021)

Improving Reproducibility in Machine Learning Research(A Report from the NeurIPS 2019 Reproducibility Program). - Joelle Pineau; Philippe Vincent-Lamarre; Koustuv Sinha; Vincent Larivière; Alina Beygelzimer; Florence d'Alché-Buc; Emily B. Fox; Hugo Larochelle (J. Mach. Learn. Res., 2021)

It's complicated: characterizing the time-varying relationship between cell phone mobility and COVID-19 spread in the US. - Sean Jewell; Joseph Futoma; Lauren Hannah; Andrew C. Miller; Nicholas J. Foti; Emily B. Fox (npj Digit. Medicine, 2021)

The Convex Mixture Distribution: Granger Causality for Categorical Time Series. - Alex Tank; Xiudi Li; Emily B. Fox; Ali Shojaie (SIAM J. Math. Data Sci., 2021)

Neural Granger Causality. - Alex Tank; Ian Covert; Nicholas J. Foti; Ali Shojaie; Emily B. Fox (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

Sequence Modeling with Multiresolution Convolutional Memory. - Jiaxin Shi; Ke Alexander Wang; Emily B. Fox (ICML, 2023)

Interpretable Mechanistic Representations for Meal-level Glycemic Control in the Wild. - Ke Alexander Wang; Emily B. Fox (ML4H@NeurIPS, 2023)

Learning Absorption Rates in Glucose-Insulin Dynamics from Meal Covariates. - Ke Alexander Wang; Matthew E. Levine; Jiaxin Shi; Emily B. Fox (CoRR, 2023)

Automated Statistical Model Discovery with Language Models. - Michael Y. Li; Emily B. Fox; Noah D. Goodman (ICML, 2024)

Hybrid2 Neural ODE Causal Modeling and an Application to Glycemic Response. - Bob Junyi Zou; Matthew E. Levine; Dessi P. Zaharieva; Ramesh Johari; Emily B. Fox (ICML, 2024)

Hybrid Square Neural ODE Causal Modeling. - Bob Junyi Zou; Matthew E. Levine; Dessi P. Zaharieva; Ramesh Johari; Emily B. Fox (CoRR, 2024)

How to Build the Virtual Cell with Artificial Intelligence: Priorities and Opportunities. - Charlotte Bunne; Yusuf Roohani; Yanay Rosen; Ankit Gupta; Xikun Zhang 001; Marcel Roed; Theo Alexandrov; Mohammed AlQuraishi; Patricia Brennan; Daniel B. Burkhardt; Andrea Califano; Jonah Cool; et al. (CoRR, 2024)