Emily Beth Fox
Stanford University
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Publication Types:
All types ( 93 )
Book chapter ( 1 )
Clinical abstract ( 2 )
Conference paper ( 34 )
Journal paper ( 36 )
Other publication ( 4 )
Preprint ( 3 )
Thesis ( 2 )
Workshop paper ( 13 )
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Hybrid^2 Neural ODE Causal Modeling
Conference paper
Bob Junyi Zou, Matthew E. Levine, Dessi P. Zaharieva, Ramesh Johari, Emily B. Fox
To appear in International Conference on Machine Learning (ICML)
Publication year: 2024
Automated Statistical Model Discovery with Language Models
Conference paper
Michael Y. Li, Emily B. Fox, Noah D. Goodman
To appear in International Conference on Machine Learning (ICML)
Publication year: 2024
Sequence Modeling with Multiresolution Convolutional Memory
Conference paper
Jiaxin Shi, Ke Alex Wang, Emily B. Fox
International Conference on Machine Learning (ICML)
Publication year: 2023
Interpretable Mechanistic Representations for Meal-level Glycemic Control in the Wild
Conference paper
Ke Alexander Wang and Emily B. Fox
Machine Learning for Health (ML4H) Symposium 2023
Publication year: 2023
Model-based metrics: Sample-efficient estimates of predictive model subpopulation performance
Conference paper
Andrew C. Miller, Leon A. Gatys, Joseph Futoma, Emily B. Fox
Proceedings of Machine Learning for Healthcare (MLHC)
Publication year: 2021
Learning Insulin-Glucose Dynamics in the Wild
Conference paper
Andrew Miller, Nicholas Foti, and Emily B. Fox
Proceedings of Machine Learning for Healthcare (MLHC)
Publication year: 2020
Adaptively Truncating Backpropagation Through Time to Control Gradient Bias
Conference paper
Christopher Aicher, Nicholas Foti, and Emily B. Fox
Proc. Conference on Uncertainty in Artificial Intelligence
Publication year: 2019
A Simple Adaptive Tracker with Reminiscences
Conference paper
Christopher Xie, Emily Fox, and Zaid Harchaoui
Proc. IEEE International Conference on Robotics and Automation
Publication year: 2019
oi-VAE: Output Interpretable VAEs for Nonlinear Group Factor Analysis
Conference paper
Samuel Ainsworth, Nicholas Foti, Adrian KC Lee, Emily B. Fox
International Conference on Machine Learning (ICML)
Publication year: 2018
Large-Scale Stochastic Sampling from the Probability Simplex
Conference paper
Jack Baker, Paul Fearnhead, Emily B. Fox, and Chris Nemeth
Advances in Neural Information Processing Systems 31 (NeurIPS 2018)
Publication year: 2018
Stochastic Gradient MCMC Methods for Hidden Markov Models
Conference paper
Yi-An Ma, Nicholas Foti, & Emily B. Fox
International Conference on Machine Learning (ICML)
Publication year: 2017
A Complete Recipe for Stochastic Gradient MCMC
Conference paper
Yi-An Ma, Tianqi Chen, & Emily B. Fox
Advances in Neural Information Processing Systems 28 (NIPS 2015)
Publication year: 2016
Streaming Variational Inference for Bayesian Nonparametric Mixture Models
Conference paper
Alex Tank, Nicholas Foti, & Emily B. Fox
International Conference on Artificial Intelligence and Statistics (AISTATS)
Publication year: 2015
Stochastic Variational Inference for Hidden Markov Models
Conference paper
Nicholas Foti, Jason Xu, Dillon Laird, & Emily B. Fox
Advances in Neural Information Processing Systems 27 (NIPS 2014)
Publication year: 2015
Expectation-Maximization for Learning Determinantal Point Processes
Conference paper
Jennifer Gillenwater, Alex Kuleza, Emily B. Fox, & Ben Taskar
Advances in Neural Information Processing Systems 27 (NIPS 2014)
Publication year: 2015
Bayesian Structure Learning for Stationary Time Series
Conference paper
Alex Tank, Nicholas Foti, & Emily B. Fox
Conference on Uncertainty in Artificial Intelligence (UAI)
Publication year: 2015
Stochastic Gradient Hamiltonian Monte Carlo
Conference paper
Tianqi Chen, Emily B. Fox, & Carlos E. Guestrin
International Conference on Machine Learning (ICML)
Publication year: 2014
Learning the Parameters of Determinantal Point Process Kernels
Conference paper
Raja Hafiz Affandi, Emily B. Fox, Ryan P. Adams, & Ben Taskar
International Conference on Machine Learning (ICML)
Publication year: 2014
Approximate Inference in Continuous Determinant Point Processes
Conference paper
Raja H. Affandi, Emily B. Fox, & Ben Taskar
Advances in Neural Information Processing Systems 26 (NIPS 2013)
Publication year: 2014
Representing Documents Through Their Readers
Conference paper
Khalid El-Arini, Min Xu, Emily B. Fox, & Carlos E. Guestrin
Conference on Knowledge Discovery and Data Mining (KDD)
Publication year: 2013
Parsing Epileptic Events Using a Markov Switching Process Model for Correlated Time Series
Conference paper
Drausin Wulsin, Emily B. Fox, & Brian Litt
International Conference on Machine Learning (ICML)
Publication year: 2013
Nystrom Approximation for Large-Scale Determinantal Processes
Conference paper
Raja H. Affandi, Alex Kulesza, Emily B. Fox, & Ben Taskar
International Conference on Artificial Intelligence and Statistics (AISTATS)
Publication year: 2013
Multiresolution Gaussian Processes
Conference paper
Emily B. Fox and David B. Dunson
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
Michael C. Hughes, Emily B. Fox, & Erik B. Sudderth
Advances in Neural Information Processing Systems 25 (NIPS 2012)
Publication year: 2013
Markov Determinantal Point Processes
Conference paper
Raja H. Affandi, Alex Kulesza, & Emily B. Fox
Conference on Uncertainty in Artificial Intelligence (UAI)
Publication year: 2012
Hierarchical Latent Dictionaries for Models of Brain Activation
Conference paper
Alona M. Fyshe, Emily B. Fox, David B. Dunson, & Tom M. Mitchell
International Conference on Artificial Intelligence and Statistics (AISTATS)
Publication year: 2012
Sharing Features among Dynamical Systems with Beta Processes
Conference paper
Emily B. Fox, Erik B. Sudderth, Michael I. Jordan, & Alan S. Willsky
Advances in Neural Information Processing Systems 22 (NIPS 2009)
Publication year: 2010
Nonparametric Bayesian Learning of Switching Linear Dynamical Systems
Conference paper
Emily B. Fox, Erik B. Sudderth, Michael I. Jordan, & Alan S. Willsky
Advances in Neural Information Processing Systems 21 (NIPS 2008)
Publication year: 2009
Nonparametric Bayesian Identification of Jump Systems with Sparse Dependencies
Conference paper
Emily B. Fox, Erik B. Sudderth, Michael I. Jordan, & Alan S. Willsky
IFAC Symposium on System Identification
Publication year: 2009
An HDP-HMM for Systems with State Persistence
Conference paper
Emily B. Fox, Erik B. Sudderth, Michael I. Jordan, & Alan S. Willsky
International Conference on Machine Learning (ICML)
Publication year: 2008
Tracking a Non-cooperative Maneuvering Target using Hierarchical Dirichlet Processes
Conference paper
E.B. Fox, E.B. Sudderth, D.S. Choi, A.S. Willsky
Adaptive Sensor Array Processing Conference
Publication year: 2007
Hierarchical Dirichlet Processes for Tracking Maneuvering Targets
Conference paper
Emily B. Fox, Erik B. Sudderth, & Alan S. Willsky
International Conference on Information Fusion (FUSION)
Publication year: 2007
Nonparametric Bayesian Methods for Large Scale Multi-Target Tracking
Conference paper
Emily B. Fox, David S. Choi, & Alan S. Willsky
Asilomar Conference On Signals, Systems, and Computers
Publication year: 2006
Detection and Localization of Material Releases with Sparse Sensor Configurations
Conference paper
Emily B. Fox, Jason L. Williams, John W. Fisher, & Alan S. Willsky
IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)
Publication year: 2006