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Emily B. Fox
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- affiliation: University of Washington, Department of Statistics
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2020 – today
- 2024
- [c31]Michael Y. Li, Emily B. Fox, Noah D. Goodman:
Automated Statistical Model Discovery with Language Models. ICML 2024 - [c30]Bob Junyi Zou, Matthew E. Levine, Dessi P. Zaharieva, Ramesh Johari, Emily B. Fox:
Hybrid2 Neural ODE Causal Modeling and an Application to Glycemic Response. ICML 2024 - [i31]Bob Junyi Zou, Matthew E. Levine, Dessi P. Zaharieva, Ramesh Johari, Emily B. Fox:
Hybrid Square Neural ODE Causal Modeling. CoRR abs/2402.17233 (2024) - [i30]Michael Y. Li, Emily B. Fox, Noah D. Goodman:
Automated Statistical Model Discovery with Language Models. CoRR abs/2402.17879 (2024) - [i29]Charlotte Bunne, Yusuf Roohani, Yanay Rosen, Ankit Gupta, Xikun Zhang, Marcel Roed, Theo Alexandrov, Mohammed AlQuraishi, Patricia Brennan, Daniel B. Burkhardt, Andrea Califano, Jonah Cool, Abby F. Dernburg, Kirsty Ewing, Emily B. Fox, Matthias Haury, Amy E. Herr, Eric Horvitz, Patrick D. Hsu, Viren Jain, Gregory R. Johnson, Thomas Kalil, David R. Kelley, Shana O. Kelley, Anna Kreshuk, Tim Mitchison, Stephani Otte, Jay Shendure, Nicolas J. Sofroniew, Fabian J. Theis, Christina V. Theodoris, Srigokul Upadhyayula, Marc Valer, Bo Wang, Eric Xing, Serena Yeung-Levy, Marinka Zitnik, Theofanis Karaletsos, Aviv Regev, Emma Lundberg, Jure Leskovec, Stephen R. Quake:
How to Build the Virtual Cell with Artificial Intelligence: Priorities and Opportunities. CoRR abs/2409.11654 (2024) - 2023
- [c29]Jiaxin Shi, Ke Alexander Wang, Emily B. Fox:
Sequence Modeling with Multiresolution Convolutional Memory. ICML 2023: 31312-31327 - [c28]Ke Alexander Wang, Emily B. Fox:
Interpretable Mechanistic Representations for Meal-level Glycemic Control in the Wild. ML4H@NeurIPS 2023: 607-622 - [i28]Ke Alexander Wang, Matthew E. Levine, Jiaxin Shi, Emily B. Fox:
Learning Absorption Rates in Glucose-Insulin Dynamics from Meal Covariates. CoRR abs/2304.14300 (2023) - [i27]Jiaxin Shi, Ke Alexander Wang, Emily B. Fox:
Sequence Modeling with Multiresolution Convolutional Memory. CoRR abs/2305.01638 (2023) - [i26]Ke Alexander Wang, Emily B. Fox:
Interpretable Mechanistic Representations for Meal-level Glycemic Control in the Wild. CoRR abs/2312.03344 (2023) - 2022
- [j13]Alex Tank
, Ian Covert
Neural Granger Causality. IEEE Trans. Pattern Anal. Mach. Intell. 44(8): 4267-4279 (2022) - 2021
- [j12]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: 164:1-164:20 (2021) - [j11]Sean Jewell
It's complicated: characterizing the time-varying relationship between cell phone mobility and COVID-19 spread in the US. npj Digit. Medicine 4 (2021) - [j10]Alex Tank
The Convex Mixture Distribution: Granger Causality for Categorical Time Series. SIAM J. Math. Data Sci. 3(1): 83-112 (2021) - [c27]Andrew C. Miller, Leon A. Gatys, Joseph Futoma, Emily B. Fox:
Model-based metrics: Sample-efficient estimates of predictive model subpopulation performance. MLHC 2021: 308-336 - [i25]Andrew C. Miller, Nicholas J. Foti, Emily B. Fox:
Breiman's two cultures: You don't have to choose sides. CoRR abs/2104.12219 (2021) - [i24]Andrew C. Miller, Leon A. Gatys, Joseph Futoma, Emily B. Fox:
Model-based metrics: Sample-efficient estimates of predictive model subpopulation performance. CoRR abs/2104.12231 (2021) - [i23]Ali Shojaie, Emily B. Fox:
Granger Causality: A Review and Recent Advances. CoRR abs/2105.02675 (2021) - 2020
- [c26]Andrew C. Miller, Nicholas J. Foti, Emily B. Fox:
Learning Insulin-Glucose Dynamics in the Wild. MLHC 2020: 172-197 - [i22]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 abs/2003.12206 (2020) - [i21]Andrew C. Miller, Nicholas J. Foti, Emily B. Fox:
Learning Insulin-Glucose Dynamics in the Wild. CoRR abs/2008.02852 (2020) - [i20]Jeffrey Chan, Andrew C. Miller, Emily B. Fox:
Representing and Denoising Wearable ECG Recordings. CoRR abs/2012.00110 (2020)
2010 – 2019
- 2019
- [j9]Yi-An Ma
Irreversible samplers from jump and continuous Markov processes. Stat. Comput. 29(1): 177-202 (2019) - [j8]Jack Baker
Control variates for stochastic gradient MCMC. Stat. Comput. 29(3): 599-615 (2019) - [j7]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): 555-587 (2019) - [c25]Christopher Xie, Emily B. Fox, Zaïd Harchaoui:
A Simple Adaptive Tracker with Reminiscences. ICRA 2019: 6596-6603 - [c24]Christopher Aicher, Nicholas J. Foti, Emily B. Fox:
Adaptively Truncating Backpropagation Through Time to Control Gradient Bias. UAI 2019: 799-808 - [e1]Hanna M. Wallach, Hugo Larochelle, Alina Beygelzimer, Florence d'Alché-Buc, Emily B. Fox, Roman Garnett:
Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, NeurIPS 2019, December 8-14, 2019, Vancouver, BC, Canada. 2019 [contents] - [i19]Christopher Aicher, Srshti Putcha, Christopher Nemeth
Stochastic Gradient MCMC for Nonlinear State Space Models. CoRR abs/1901.10568 (2019) - [i18]Christopher Aicher, Nicholas J. Foti, Emily B. Fox:
Adaptively Truncating Backpropagation Through Time to Control Gradient Bias. CoRR abs/1905.07473 (2019) - [i17]Jonas Rauber, Emily B. Fox, Leon A. Gatys:
Modeling patterns of smartphone usage and their relationship to cognitive health. CoRR abs/1911.05683 (2019) - 2018
- [c23]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: 119-128 - [c22]Jack Baker, Paul Fearnhead, Emily B. Fox, Christopher Nemeth:
Large-Scale Stochastic Sampling from the Probability Simplex. NeurIPS 2018: 6722-6732 - [i16]Samuel K. Ainsworth, Nicholas J. Foti, Adrian K. C. Lee, Emily B. Fox:
Interpretable VAEs for nonlinear group factor analysis. CoRR abs/1802.06765 (2018) - [i15]Jack Baker, Paul Fearnhead
Large-Scale Stochastic Sampling from the Probability Simplex. CoRR abs/1806.07137 (2018) - [i14]Samuel K. Ainsworth, Nicholas J. Foti, Emily B. Fox:
Disentangled VAE Representations for Multi-Aspect and Missing Data. CoRR abs/1806.09060 (2018) - [i13]Christopher Aicher, Emily B. Fox:
Approximate Collapsed Gibbs Clustering with Expectation Propagation. CoRR abs/1807.07621 (2018) - [i12]Christopher Aicher, Yi-An Ma, Nicholas J. Foti, Emily B. Fox:
Stochastic Gradient MCMC for State Space Models. CoRR abs/1810.09098 (2018) - 2017
- [c21]Yi-An Ma, Nicholas J. Foti, Emily B. Fox:
Stochastic Gradient MCMC Methods for Hidden Markov Models. ICML 2017: 2265-2274 - [i11]Jack Baker, Paul Fearnhead
Control Variates for Stochastic Gradient MCMC. CoRR abs/1706.05439 (2017) - [i10]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 abs/1710.08473 (2017) - 2015
- [j6]Emily B. Fox, David B. Dunson:
Bayesian nonparametric covariance regression. J. Mach. Learn. Res. 16: 2501-2542 (2015) - [j5]Ryan P. Adams, Emily B. Fox
Guest Editors' Introduction to the Special Issue on Bayesian Nonparametrics. IEEE Trans. Pattern Anal. Mach. Intell. 37(2): 209-211 (2015) - [c20]Alex Tank, Nicholas J. Foti, Emily B. Fox:
Streaming Variational Inference for Bayesian Nonparametric Mixture Models. AISTATS 2015 - [c19]Yi-An Ma, Tianqi Chen, Emily B. Fox:
A Complete Recipe for Stochastic Gradient MCMC. NIPS 2015: 2917-2925 - [c18]Alex Tank, Nicholas J. Foti, Emily B. Fox:
Bayesian Structure Learning for Stationary Time Series. UAI 2015: 872-881 - 2014
- [j4]Drausin F. Wulsin, Emily B. Fox
Modeling the complex dynamics and changing correlations of epileptic events. Artif. Intell. 216: 55-75 (2014) - [c17]Raja Hafiz Affandi, Emily B. Fox, Ryan P. Adams, Benjamin Taskar:
Learning the Parameters of Determinantal Point Process Kernels. ICML 2014: 1224-1232 - [c16]Tianqi Chen, Emily B. Fox, Carlos Guestrin:
Stochastic Gradient Hamiltonian Monte Carlo. ICML 2014: 1683-1691 - [c15]Jennifer Gillenwater, Alex Kulesza, Emily B. Fox, Benjamin Taskar:
Expectation-Maximization for Learning Determinantal Point Processes. NIPS 2014: 3149-3157 - [c14]Nicholas J. Foti, Jason Xu, Dillon Laird, Emily B. Fox:
Stochastic variational inference for hidden Markov models. NIPS 2014: 3599-3607 - [r1]Emily B. Fox, Michael I. Jordan:
Mixed Membership Models for Time Series. Handbook of Mixed Membership Models and Their Applications 2014: 417-439 - [i9]Francois Caron, Emily B. Fox:
Bayesian nonparametric models of sparse and exchangeable random graphs. CoRR abs/1401.1137 (2014) - [i8]Tianqi Chen, Emily B. Fox, Carlos Guestrin:
Stochastic Gradient Hamiltonian Monte Carlo. CoRR abs/1402.4102 (2014) - [i7]Raja Hafiz Affandi, Emily B. Fox, Ryan P. Adams, Ben Taskar:
Learning the Parameters of Determinantal Point Process Kernels. CoRR abs/1402.4862 (2014) - [i6]Jennifer Gillenwater, Alex Kulesza, Emily B. Fox, Ben Taskar:
Expectation-Maximization for Learning Determinantal Point Processes. CoRR abs/1411.1088 (2014) - 2013
- [c13]Raja Hafiz Affandi, Alex Kulesza, Emily B. Fox, Ben Taskar:
Nystrom Approximation for Large-Scale Determinantal Processes. AISTATS 2013: 85-98 - [c12]Drausin Wulsin, Emily B. Fox, Brian Litt:
Parsing epileptic events using a Markov switching process model for correlated time series. ICML (1) 2013: 356-364 - [c11]Khalid El-Arini, Min Xu, Emily B. Fox, Carlos Guestrin:
Representing documents through their readers. KDD 2013: 14-22 - [c10]Raja Hafiz Affandi, Emily B. Fox, Ben Taskar:
Approximate Inference in Continuous Determinantal Processes. NIPS 2013: 1430-1438 - [i5]Tauhid Zaman, Emily B. Fox, Eric T. Bradlow:
A Bayesian Approach for Predicting the Popularity of Tweets. CoRR abs/1304.6777 (2013) - [i4]Emily B. Fox, Michael I. Jordan:
Mixed Membership Models for Time Series. CoRR abs/1309.3533 (2013) - [i3]Raja Hafiz Affandi, Emily B. Fox, Ben Taskar:
Approximate Inference in Continuous Determinantal Point Processes. CoRR abs/1311.2971 (2013) - 2012
- [c9]Emily B. Fox, David B. Dunson:
Multiresolution Gaussian Processes. NIPS 2012: 746-754 - [c8]Michael C. Hughes, Emily B. Fox, Erik B. Sudderth:
Effective Split-Merge Monte Carlo Methods for Nonparametric Models of Sequential Data. NIPS 2012: 1304-1312 - [c7]Raja Hafiz Affandi, Alex Kulesza, Emily B. Fox:
Markov Determinantal Point Processes. UAI 2012: 26-35 - [c6]Alona Fyshe, Emily B. Fox, David B. Dunson, Tom M. Mitchell:
Hierarchical Latent Dictionaries for Models of Brain Activation. AISTATS 2012: 409-421 - [i2]Khalid El-Arini, Emily B. Fox, Carlos Guestrin:
Concept Modeling with Superwords. CoRR abs/1204.2523 (2012) - [i1]Raja Hafiz Affandi, Alex Kulesza, Emily B. Fox:
Markov Determinantal Point Processes. CoRR abs/1210.4850 (2012) - 2011
- [j3]Emily B. Fox
Bayesian Nonparametric Inference of Switching Dynamic Linear Models. IEEE Trans. Signal Process. 59(4): 1569-1585 (2011) - 2010
- [j2]Emily B. Fox
Bayesian Nonparametric Methods for Learning Markov Switching Processes. IEEE Signal Process. Mag. 27(6): 43-54 (2010)
2000 – 2009
- 2009
- [b1]Emily B. Fox:
Bayesian nonparametric learning of complex dynamical phenomena. Massachusetts Institute of Technology, Cambridge, MA, USA, 2009 - [c5]Emily B. Fox, Erik B. Sudderth, Michael I. Jordan, Alan S. Willsky:
Sharing Features among Dynamical Systems with Beta Processes. NIPS 2009: 549-557 - 2008
- [c4]Emily B. Fox, Erik B. Sudderth
An HDP-HMM for systems with state persistence. ICML 2008: 312-319 - [c3]Emily B. Fox, Erik B. Sudderth, Michael I. Jordan, Alan S. Willsky:
Nonparametric Bayesian Learning of Switching Linear Dynamical Systems. NIPS 2008: 457-464 - 2007
- [j1]Emily B. Fox, John W. Fisher III
Detection and Localization of Material Releases With Sparse Sensor Configurations. IEEE Trans. Signal Process. 55(5-1): 1886-1898 (2007) - [c2]Emily B. Fox, Erik B. Sudderth
Hierarchical Dirichlet processes for tracking maneuvering targets. FUSION 2007: 1-8 - 2006
- [c1]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: 945-948
Coauthor Index
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last updated on 2024-10-23 20:32 CEST by the dblp team
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