Emily Beth Fox
Stanford University
Publications
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Using a Linear Dynamic System to Measure Functional Connectivity from M/EEG
Smart Start: Designing Powerful Clinical Trials Using Pilot Study Data
Hybrid^2 Neural ODE Causal Modeling
Conference paper
To appear in International Conference on Machine Learning (ICML)
Publication year: 2024
Automated Statistical Model Discovery with Language Models
Conference paper
To appear in International Conference on Machine Learning (ICML)
Publication year: 2024
The Evolving Role of Data & Safety Monitoring Boards for Real-World Clinical Trials
Journal paper
Journal of Clinical and Translational Science, Volume 7, Issue 1
Publication year: 2023
Stochastic Gradient MCMC for Nonlinear State Space Models
Sequence Modeling with Multiresolution Convolutional Memory
Interpretable Mechanistic Representations for Meal-level Glycemic Control in the Wild
Adding glycemic and physical activity metrics to a multimodal algorithm-enabled decision-support tool for type 1 diabetes care: Keys to implementation and opportunities
A Pharmacokinetic Model of Anti-Seizure Medication Load to Guide Care in the Epilepsy Monitoring Unit
The Association between Patient Characteristics and the Efficacy of Remote Patient Monitoring and Messaging
Statistical Deconvolution for Inference of Infection Time Series
Learning Absorption Rates in Glucose-Insulin Dynamics from Meal Covariates
Granger Causality: A Review and Recent Advances
Journal paper
Annual Review of Statistics and its Application, Volume 9, Pages 289-319
Publication year: 2022
A Platform for the Personalized Management of Diabetes and Cardiovascular Disease at Population Scale With Data From Multiple Sensors
The Convex Mixture Distribution: Granger Causality for Categorical Time Series
Journal paper
SIAM Journal on Mathematics of Data Science, Volume 3, Issue 1, Pages 83-112
Publication year: 2021
Neural Granger Causality for Nonlinear Time Series
Journal paper
IEEE Transaction on Pattern Analysis and Machine Intelligence, Volume 44, Issue 8, Pages 4267-4279
Publication year: 2021
Model-based metrics: Sample-efficient estimates of predictive model subpopulation performance
It's complicated: characterizing the time-varying relationship between cell phone mobility and COVID-19 spread in the US
Improving Reproducibility in Machine Learning Research (A Report from the NeurIPS 2019 Reproducibility Program)
Journal paper
Journal of Machine Learning Research, Volume 22, Issue 164, Pages 1-20
Publication year: 2021
Breiman's two cultures: You don't have to choose sides
Representing and Denoising Wearable ECG Recordings
Mobility trends provide a leading indicator of changes in SARS-CoV-2 transmission
Learning Insulin-Glucose Dynamics in the Wild
Stochastic Gradient MCMC for State Space Models
Journal paper
SIAM Journal on Mathematics of Data Science, Volume 1, Issue 3, Pages 555-587
Publication year: 2019
Statistical Model-based Approaches for Functional Connectivity Analysis of Neuroimaging Data
Modeling Patterns of Smartphone Usage and Their Relationship to Cognitive Health
Irreversible Samplers from Jump and Continuous Markov Processes
Identifiability and Estimation of Structural Vector Autoregressive Models for Subsampled and Mixed Frequency Time Series.
Control Variates for Stochastic Gradient MCMC
Adaptively Truncating Backpropagation Through Time to Control Gradient Bias
A Simple Adaptive Tracker with Reminiscences
Conference paper
Proc. IEEE International Conference on Robotics and Automation
Publication year: 2019
sgmcmc: An R Package for Stochastic Gradient Markov Chain Monte Carlo
Journal paper
Journal of Statistical Software, Volume 91, Issue 3, Pages 1-27
Publication year: 2018
oi-VAE: Output Interpretable VAEs for Nonlinear Group Factor Analysis
Large-Scale Stochastic Sampling from the Probability Simplex
Conference paper
Advances in Neural Information Processing Systems 31 (NeurIPS 2018)
Publication year: 2018
Dynamics of Homelessness in Urban America
Journal paper
Annals of Applied Statistics, Volume 13, Number 1, Pages 573-605
Publication year: 2018
Disentangled VAE Representations for Multi-Aspect and Missing Data
Comment: Nonparametric Bayes Modeling of Populations of Networks
Journal paper
Journal of the American Statistical Association, Vol. 112, No. 520, pp. 1539-1543
Publication year: 2018
Stochastic Gradient MCMC Methods for Hidden Markov Models
Sparse Graphs using Exchangeable Random Measures
Journal paper
Journal of the Royal Statistical Society: Series B (read paper), Vol. 79, No. 5, pp. 1295-1366
Publication year: 2017
Clustering Correlated, Sparse Data Streams to Estimate a Localized Housing Price Index
An Interpretable and Sparse Neural Network Model for Nonlinear Granger Causality Discovery
An Efficient ADMM Algorithm for Structural Break Detection in Multivariate Time Series
Temporal Behavior of Seizures and Interictal Bursts in Prolonged Intracranial Recordings from Epileptic Canines
Spatio-Temporal Low Count Processes with Application to Violent Crime Events
Sparse plus low-rank graphical models of time series for functional connectivity in MEG
Scalable Clustering of Correlated Time Series using Expectation Propagation
Mining Continuous Intracranial EEG in Focal Canine Epilepsy: Relating Intracranial Bursts to Seizure Onsets
Identifiability of Non-Gaussian Structural VAR Models for Subsampled and Mixed Frequency Time Series
Granger Causality Networks for Categorical Time Series
A Unified Framework for Missing Data and Cold Start Prediction for Time Series Data
A Novel Seizure Detection Algorithm Informed by Hidden Markov Model Event States
A Complete Recipe for Stochastic Gradient MCMC
Conference paper
Advances in Neural Information Processing Systems 28 (NIPS 2015)
Publication year: 2016
Streaming Variational Inference for Bayesian Nonparametric Mixture Models
Conference paper
International Conference on Artificial Intelligence and Statistics (AISTATS)
Publication year: 2015
Stochastic Variational Inference for Hidden Markov Models
Conference paper
Advances in Neural Information Processing Systems 27 (NIPS 2014)
Publication year: 2015
Mixed Membership Models for Time Series
Book chapter
Handbook of Mixed Membership Models and Their Applications, pp. 417-436, Chapman & Hall
Publication year: 2015
Guest Editors’ Introduction to the Special Issue on Bayesian Nonparametrics
Journal paper
IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 37, no. 2, pp. 209-211
Publication year: 2015
Expectation-Maximization for Learning Determinantal Point Processes
Conference paper
Advances in Neural Information Processing Systems 27 (NIPS 2014)
Publication year: 2015
Bayesian Structure Learning for Stationary Time Series
Bayesian Nonparametric Covariance Regression
Streaming Variational Inference for Normalized Random Measure Mixture Models
Stochastic Gradient Hamiltonian Monte Carlo
Modeling the Complex Dynamics and Changing Correlations of Epileptic Events
Learning the Parameters of Determinantal Point Process Kernels
Joint Modeling of Multiple Time Series via the Beta Process with Application to Motion Capture Segmentation
Detecting and Classifying Anomalous Behavior in Spatiotemporal Network Data
Workshop paper
KDD Workshop on Learning about Emergencies from Social Information
Publication year: 2014
Approximate Inference in Continuous Determinant Point Processes
Conference paper
Advances in Neural Information Processing Systems 26 (NIPS 2013)
Publication year: 2014
A Bayesian Approach for Predicting the Popularity of Tweets
Representing Documents Through Their Readers
Parsing Epileptic Events Using a Markov Switching Process Model for Correlated Time Series
Nystrom Approximation for Large-Scale Determinantal Processes
Conference paper
International Conference on Artificial Intelligence and Statistics (AISTATS)
Publication year: 2013
Multiresolution Gaussian Processes
Conference paper
Advances in Neural Information Processing Systems 25 (NIPS 2012)
Publication year: 2013
Effective Split-Merge Monte Carlo Methods for Nonparametric Models of Sequence Data
Conference paper
Advances in Neural Information Processing Systems 25 (NIPS 2012)
Publication year: 2013
Markov Determinantal Point Processes
Hierarchical Latent Dictionaries for Models of Brain Activation
Conference paper
International Conference on Artificial Intelligence and Statistics (AISTATS)
Publication year: 2012
Bayesian Nonparametric Inference of Switching Dynamic Linear Models
Journal paper
IEEE Transactions on Signal Processing, vol. 59, no. 4, pp. 1569-1585
Publication year: 2011
Autoregressive Models for Variance Matrices: Stationary Inverse Wishart Processes
A Sticky HDP-HMM with Application to Speaker Diarization
Sharing Features among Dynamical Systems with Beta Processes
Conference paper
Advances in Neural Information Processing Systems 22 (NIPS 2009)
Publication year: 2010
Bayesian Nonparametric Methods for Learning Markov Switching Processes
Nonparametric Bayesian Learning of Switching Linear Dynamical Systems
Conference paper
Advances in Neural Information Processing Systems 21 (NIPS 2008)
Publication year: 2009
Nonparametric Bayesian Identification of Jump Systems with Sparse Dependencies
Bayesian Nonparametric Learning of Complex Dynamical Phenomena
Nonparametric Learning of Switching Autoregressive Processes
An HDP-HMM for Systems with State Persistence
Tracking a Non-cooperative Maneuvering Target using Hierarchical Dirichlet Processes
Hierarchical Dirichlet Processes for Tracking Maneuvering Targets
Detection and Localization of Material Releases with Sparse Sensor Configurations
Journal paper
IEEE Transactions on Signal Processing, vol. 55, no. 5, pp. 1886-1898
Publication year: 2007
Nonparametric Bayesian Methods for Large Scale Multi-Target Tracking
Detection and Localization of Material Releases with Sparse Sensor Configurations
Conference paper
IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)
Publication year: 2006
Information Fusion and Uncertainty Management for Biological Multisensor Systems
Detection and Localization of Aerosol Releases from Sparse Sensor Measurements
Thesis
Publication year: 2005
Multisensor Information Fusion for Biological Sensor Networks and CBRN Detection
Other publication
Conference on Science and Technology Chem-Bio Information Systems
Publication year: 2004