Seth R. Flaxman

Publication Activity (10 Years)

Years Active: 2009-2024
Publications (10 Years): 28

Top Topics

Gaussian Process

Top Venues

Publications

Elizaveta Semenova, Swapnil Mishra, Samir Bhatt, Seth R. Flaxman, H. Juliette T. Unwin
Deep Learning and MCMC with aggVAE for Shifting Administrative Boundaries: Mapping Malaria Prevalence in Kenya. Epi UAI (2024)
Makkunda Sharma, Fan Yang, Duy-Nhat Vo, Esra Suel, Swapnil Mishra, Samir Bhatt, Oliver Fiala, William Rudgard, Seth R. Flaxman
KidSat: satellite imagery to map childhood poverty dataset and benchmark. CoRR (2024)
Elizaveta Semenova, Max Cairney-Leeming, Seth R. Flaxman
PriorCVAE: scalable MCMC parameter inference with Bayesian deep generative modelling. CoRR (2023)
Giovanni Charles, Timothy M. Wolock, Peter Winskill, Azra C. Ghani, Samir Bhatt, Seth R. Flaxman
Seq2Seq Surrogates of Epidemic Models to Facilitate Bayesian Inference. AAAI (2023)
Stamatina Lamprinakou, Mauricio Barahona, Seth R. Flaxman, Sarah Filippi, Axel Gandy, Emma J. McCoy
BART-based inference for Poisson processes. Comput. Stat. Data Anal. 180 (2023)
Xenia Miscouridou, Samir Bhatt, George O. Mohler, Seth R. Flaxman, Swapnil Mishra
Cox-Hawkes: doubly stochastic spatiotemporal Poisson processes. Trans. Mach. Learn. Res. 2023 (2023)
Elizaveta Semenova, Swapnil Mishra, Samir Bhatt, Seth R. Flaxman, H. Juliette T. Unwin
Deep learning and MCMC with aggVAE for shifting administrative boundaries: mapping malaria prevalence in Kenya. CoRR (2023)
Qinyi Zhang, Veit Wild, Sarah Filippi, Seth R. Flaxman, Dino Sejdinovic
Bayesian Kernel Two-Sample Testing. J. Comput. Graph. Stat. 31 (4) (2022)
Andrew J. Holbrook, Charles E. Loeffler, Seth R. Flaxman, Marc A. Suchard
Scalable Bayesian inference for self-excitatory stochastic processes applied to big American gunfire data. Stat. Comput. 31 (1) (2021)
Stamatina Lamprinakou, Emma J. McCoy, Mauricio Barahona, Axel Gandy, Seth R. Flaxman, Sarah Filippi
BART-based inference for Poisson processes. CoRR (2020)
Jonathan Ish-Horowicz, Dana Udwin, Seth R. Flaxman, Sarah Filippi, Lorin Crawford
Interpreting Deep Neural Networks Through Variable Importance. CoRR (2019)
Ho Chung Leon Law, Dino Sejdinovic, Ewan Cameron, Tim C. D. Lucas, Seth R. Flaxman, Katherine Battle, Kenji Fukumizu
Variational Learning on Aggregate Outputs with Gaussian Processes. CoRR (2018)
Anthony Hu, Seth R. Flaxman
Multimodal Sentiment Analysis To Explore the Structure of Emotions. KDD (2018)
Gabriele Abbati, Alessandra Tosi, Michael A. Osborne, Seth R. Flaxman
AdaGeo: Adaptive Geometric Learning for Optimization and Sampling. AISTATS (2018)
Ho Chung Leon Law, Danica J. Sutherland, Dino Sejdinovic, Seth R. Flaxman
Bayesian Approaches to Distribution Regression. AISTATS (2018)
Ho Chung Leon Law, Dino Sejdinovic, Ewan Cameron, Tim C. D. Lucas, Seth R. Flaxman, Katherine Battle, Kenji Fukumizu
Variational Learning on Aggregate Outputs with Gaussian Processes. NeurIPS (2018)
Anthony Hu, Seth R. Flaxman
Multimodal Sentiment Analysis To Explore the Structure of Emotions. CoRR (2018)
Seth R. Flaxman, Yee Whye Teh, Dino Sejdinovic
Poisson intensity estimation with reproducing kernels. AISTATS (2017)
Ho Chung Leon Law, Danica J. Sutherland, Dino Sejdinovic, Seth R. Flaxman
Bayesian Distribution Regression. CoRR (2017)
Bryce Goodman, Seth R. Flaxman
European Union Regulations on Algorithmic Decision-Making and a "Right to Explanation". AI Mag. 38 (3) (2017)
Qinyi Zhang, Sarah Filippi, Seth R. Flaxman, Dino Sejdinovic
Feature-to-Feature Regression for a Two-Step Conditional Independence Test. UAI (2017)
Seth R. Flaxman, Daniel B. Neill, Alexander J. Smola
Gaussian Processes for Independence Tests with Non-iid Data in Causal Inference. ACM Trans. Intell. Syst. Technol. 7 (2) (2016)
Seth R. Flaxman, Dino Sejdinovic, John P. Cunningham, Sarah Filippi
Bayesian Learning of Kernel Embeddings. UAI (2016)
William Herlands, Andrew Gordon Wilson, Hannes Nickisch, Seth R. Flaxman, Daniel B. Neill, Wilbert Van Panhuis, Eric P. Xing
Scalable Gaussian Processes for Characterizing Multidimensional Change Surfaces. AISTATS (2016)
Bryce Goodman, Seth R. Flaxman
EU regulations on algorithmic decision-making and a "right to explanation". CoRR (2016)
Hyunjik Kim, Xiaoyu Lu, Seth R. Flaxman, Yee Whye Teh
Tucker Gaussian Process for Regression and Collaborative Filtering. CoRR (2016)
Seth R. Flaxman, Yu-Xiang Wang, Alexander J. Smola
Who Supported Obama in 2012?: Ecological Inference through Distribution Regression. KDD (2015)
Seth R. Flaxman, Andrew Gordon Wilson, Daniel B. Neill, Hannes Nickisch, Alexander J. Smola
Fast Kronecker Inference in Gaussian Processes with non-Gaussian Likelihoods. ICML (2015)
Kevin Corcoran, Seth R. Flaxman, Mark Neyer, Peter Scherpelz, Craig Weidert, Ran Libeskind-Hadas
Approximation Algorithms for Traffic Grooming in WDM Rings. ICC (2009)