Seth R. Flaxman

55 papers A* 6A 7Journal 40Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Benchmarking Missing Data Imputation Methods in Socioeconomic Surveys. Trans. Mach. Learn. Res. Siyi Sun, David Antony Selby, Yunchuan Huang, Ayush Patnaik, Sebastian Josef Vollmer, Seth R. Flaxman, Anisoara Calinescu
2025	J	`jnl`	Artificial intelligence for modelling infectious disease epidemics. Nat. Moritz U. G. Kraemer, Joseph L.-H. Tsui, Serina Chang, Spyros Lytras, Mark P. Khurana, Samantha Vanderslott, Sumali Bajaj, Neil Scheidwasser, Jacob Liam Curran-Sebastian, Elizaveta Semenova, Mengyan Zhang, H. Juliette T. Unwin, Oliver J. Watson, Cathal Mills, Abhishek Dasgupta, Luca Ferretti, Samuel V. Scarpino, Etien Koua, Oliver Morgan, Houriiyah Tegally, Ulrich Paquet, Loukas Moutsianas, Christophe Fraser, Neil M. Ferguson, Eric J. Topol, David A. Duchêne, Tanja Stadler, Patricia Kingori, Michael J. Parker, Francesca Dominici, Nigel Shadbolt, Marc A. Suchard, Oliver Ratmann, Seth R. Flaxman, Edward C. Holmes, Manuel Gomez-Rodriguez, Bernhard Schölkopf, Christl A. Donnelly, Oliver G. Pybus, Simon Cauchemez, Samir Bhatt
2025	J	`jnl`	DeepRV: pre-trained spatial priors for accelerated disease mapping. CoRR Jhonathan Navott, Daniel Jenson, Seth R. Flaxman, Elizaveta Semenova
2025	J	`jnl`	IMAGIC-500: IMputation benchmark on A Generative Imaginary Country (500k samples). CoRR Siyi Sun, David Antony Selby, Yunchuan Huang, Sebastian J. Vollmer, Seth R. Flaxman, Anisoara Calinescu
2025	J	`jnl`	Scalable Spatiotemporal Inference with Biased Scan Attention Transformer Neural Processes. CoRR Daniel Jenson, Jhonathan Navott, Piotr Grynfelder, Mengyan Zhang, Makkunda Sharma, Elizaveta Semenova, Seth R. Flaxman
2024	—	`conf`	Deep Learning and MCMC with aggVAE for Shifting Administrative Boundaries: Mapping Malaria Prevalence in Kenya. Epi UAI Elizaveta Semenova, Swapnil Mishra, Samir Bhatt, Seth R. Flaxman, H. Juliette T. Unwin
2024	J	`jnl`	Graph Agnostic Causal Bayesian Optimisation. CoRR Sumantrak Mukherjee, Mengyan Zhang, Seth R. Flaxman, Sebastian J. Vollmer
2024	J	`jnl`	Indirect Query Bayesian Optimization with Integrated Feedback. CoRR Mengyan Zhang, Shahine Bouabid, Cheng Soon Ong, Seth R. Flaxman, Dino Sejdinovic
2024	J	`jnl`	KidSat: satellite imagery to map childhood poverty dataset and benchmark. CoRR Makkunda Sharma, Fan Yang, Duy-Nhat Vo, Esra Suel, Swapnil Mishra, Samir Bhatt, Oliver Fiala, William Rudgard, Seth R. Flaxman
2024	J	`jnl`	Numerically Stable Sparse Gaussian Processes via Minimum Separation using Cover Trees. J. Mach. Learn. Res. Alexander Terenin, David R. Burt, Artem Artemev, Seth R. Flaxman, Mark van der Wilk, Carl Edward Rasmussen, Hong Ge
2024	J	`jnl`	Transformer Neural Processes - Kernel Regression. CoRR Daniel Jenson, Jhonathan Navott, Mengyan Zhang, Makkunda Sharma, Elizaveta Semenova, Seth R. Flaxman
2024	J	`jnl`	Uncertainty-Aware Regression for Socio-Economic Estimation via Multi-View Remote Sensing. CoRR Fan Yang, Sahoko Ishida, Mengyan Zhang, Daniel Jenson, Swapnil Mishra, Jhonathan Navott, Seth R. Flaxman
2023	J	`jnl`	BART-based inference for Poisson processes. Comput. Stat. Data Anal. Stamatina Lamprinakou, Mauricio Barahona, Seth R. Flaxman, Sarah Filippi, Axel Gandy, Emma J. McCoy
2023	J	`jnl`	Cox-Hawkes: doubly stochastic spatiotemporal Poisson processes. Trans. Mach. Learn. Res. Xenia Miscouridou, Samir Bhatt, George O. Mohler, Seth R. Flaxman, Swapnil Mishra
2023	J	`jnl`	Deep learning and MCMC with aggVAE for shifting administrative boundaries: mapping malaria prevalence in Kenya. CoRR Elizaveta Semenova, Swapnil Mishra, Samir Bhatt, Seth R. Flaxman, H. Juliette T. Unwin
2023	J	`jnl`	PriorCVAE: scalable MCMC parameter inference with Bayesian deep generative modelling. CoRR Elizaveta Semenova, Max Cairney-Leeming, Seth R. Flaxman
2023	A*	`conf`	Seq2Seq Surrogates of Epidemic Models to Facilitate Bayesian Inference. AAAI Giovanni Charles, Timothy M. Wolock, Peter Winskill, Azra C. Ghani, Samir Bhatt, Seth R. Flaxman
2022	J	`jnl`	Bayesian Kernel Two-Sample Testing. J. Comput. Graph. Stat. Qinyi Zhang, Veit Wild, Sarah Filippi, Seth R. Flaxman, Dino Sejdinovic
2022	J	`jnl`	City-Wide Perceptions of Neighbourhood Quality using Street View Images. CoRR Emily Muller, Emily Gemmell, Ishmam Choudhury, Ricky Nathvani, Antje Barbara Metzler, James E. Bennett, Emily Denton, Seth R. Flaxman, Majid Ezzati
2022	J	`jnl`	Cox-Hawkes: doubly stochastic spatiotemporal Poisson processes. CoRR Xenia Miscouridou, Samir Bhatt, George O. Mohler, Seth R. Flaxman, Swapnil Mishra
2022	J	`jnl`	Numerically Stable Sparse Gaussian Processes via Minimum Separation using Cover Trees. CoRR Alexander Terenin, David R. Burt, Artem Artemev, Seth R. Flaxman, Mark van der Wilk, Carl Edward Rasmussen, Hong Ge
2022	J	`jnl`	Seq2Seq Surrogates of Epidemic Models to Facilitate Bayesian Inference. CoRR Giovanni Charles, Timothy M. Wolock, Peter Winskill, Azra C. Ghani, Samir Bhatt, Seth R. Flaxman
2022	J	`jnl`	πVAE: a stochastic process prior for Bayesian deep learning with MCMC. Stat. Comput. Swapnil Mishra, Seth R. Flaxman, Tresnia Berah, Harrison Zhu, Mikko S. Pakkanen, Samir Bhatt
2021	J	`jnl`	Encoding spatiotemporal priors with VAEs for small-area estimation. CoRR Elizaveta Semenova, Yidan Xu, Adam Howes, Theo Rashid, Samir Bhatt, Swapnil Mishra, Seth R. Flaxman
2021	A	`conf`	Gaussian process nowcasting: application to COVID-19 mortality reporting. UAI Iwona Hawryluk, Henrique Hoeltgebaum, Swapnil Mishra, Xenia Miscouridou, Ricardo P. Schnekenberg, Charles Whittaker, Michaela A. C. Vollmer, Seth R. Flaxman, Samir Bhatt, Thomas A. Mellan
2021	J	`jnl`	PCACE: A Statistical Approach to Ranking Neurons for CNN Interpretability. CoRR Sílvia Casacuberta, Esra Suel, Seth R. Flaxman
2021	J	`jnl`	Scalable Bayesian inference for self-excitatory stochastic processes applied to big American gunfire data. Stat. Comput. Andrew J. Holbrook, Charles E. Loeffler, Seth R. Flaxman, Marc A. Suchard
2021	J	`jnl`	Unrepresentative big surveys significantly overestimated US vaccine uptake. Nat. Valerie C. Bradley, Shiro Kuriwaki, Michael Isakov, Dino Sejdinovic, Xiao-Li Meng, Seth R. Flaxman
2021	J	`jnl`	Using Hawkes Processes to model imported and local malaria cases in near-elimination settings. PLoS Comput. Biol. H. Juliette T. Unwin, Isobel Routledge, Seth R. Flaxman, Marian-Andrei Rizoiu, Shengjie Lai, Justin Cohen, Daniel J. Weiss, Swapnil Mishra, Samir Bhatt
2020	J	`jnl`	A unified machine learning approach to time series forecasting applied to demand at emergency departments. CoRR Michaela A. C. Vollmer, Ben Glampson, Thomas A. Mellan, Swapnil Mishra, Luca Mercuri, Ceire Costelloe, Robert Klaber, Graham S. Cooke, Seth R. Flaxman, Samir Bhatt
2020	J	`jnl`	BART-based inference for Poisson processes. CoRR Stamatina Lamprinakou, Emma J. McCoy, Mauricio Barahona, Axel Gandy, Seth R. Flaxman, Sarah Filippi
2020	A*	`conf`	Bayesian Probabilistic Numerical Integration with Tree-Based Models. NeurIPS Harrison Zhu, Xing Liu, Ruya Kang, Zhichao Shen, Seth R. Flaxman, François-Xavier Briol
2020	J	`jnl`	Bayesian Probabilistic Numerical Integration with Tree-Based Models. CoRR Harrison Zhu, Xing Liu, Ruya Kang, Zhichao Shen, Seth R. Flaxman, François-Xavier Briol
2020	J	`jnl`	Improving axial resolution in SIM using deep learning. CoRR Miguel A. Boland, Edward A. K. Cohen, Seth R. Flaxman, Mark A. A. Neil
2020	J	`jnl`	πVAE: Encoding stochastic process priors with variational autoencoders. CoRR Swapnil Mishra, Seth R. Flaxman, Samir Bhatt
2019	J	`jnl`	Interpreting Deep Neural Networks Through Variable Importance. CoRR Jonathan Ish-Horowicz, Dana Udwin, Seth R. Flaxman, Sarah Filippi, Lorin Crawford
2019	J	`jnl`	Modeling and Forecasting Art Movements with CGANs. CoRR Edoardo Lisi, Mohammad Malekzadeh, Hamed Haddadi, F. Din-Houn Lau, Seth R. Flaxman
2018	A	`conf`	AdaGeo: Adaptive Geometric Learning for Optimization and Sampling. AISTATS Gabriele Abbati, Alessandra Tosi, Michael A. Osborne, Seth R. Flaxman
2018	A	`conf`	Bayesian Approaches to Distribution Regression. AISTATS Ho Chung Leon Law, Danica J. Sutherland, Dino Sejdinovic, Seth R. Flaxman
2018	A*	`conf`	Multimodal Sentiment Analysis To Explore the Structure of Emotions. KDD Anthony Hu, Seth R. Flaxman
2018	J	`jnl`	Multimodal Sentiment Analysis To Explore the Structure of Emotions. CoRR Anthony Hu, Seth R. Flaxman
2018	A*	`conf`	Variational Learning on Aggregate Outputs with Gaussian Processes. NeurIPS Ho Chung Leon Law, Dino Sejdinovic, Ewan Cameron, Tim C. D. Lucas, Seth R. Flaxman, Katherine Battle, Kenji Fukumizu
2018	J	`jnl`	Variational Learning on Aggregate Outputs with Gaussian Processes. CoRR Ho Chung Leon Law, Dino Sejdinovic, Ewan Cameron, Tim C. D. Lucas, Seth R. Flaxman, Katherine Battle, Kenji Fukumizu
2017	J	`jnl`	Bayesian Distribution Regression. CoRR Ho Chung Leon Law, Danica J. Sutherland, Dino Sejdinovic, Seth R. Flaxman
2017	J	`jnl`	European Union Regulations on Algorithmic Decision-Making and a "Right to Explanation". AI Mag. Bryce Goodman, Seth R. Flaxman
2017	A	`conf`	Feature-to-Feature Regression for a Two-Step Conditional Independence Test. UAI Qinyi Zhang, Sarah Filippi, Seth R. Flaxman, Dino Sejdinovic
2017	A	`conf`	Poisson intensity estimation with reproducing kernels. AISTATS Seth R. Flaxman, Yee Whye Teh, Dino Sejdinovic
2016	A	`conf`	Bayesian Learning of Kernel Embeddings. UAI Seth R. Flaxman, Dino Sejdinovic, John P. Cunningham, Sarah Filippi
2016	J	`jnl`	EU regulations on algorithmic decision-making and a "right to explanation". CoRR Bryce Goodman, Seth R. Flaxman
2016	J	`jnl`	Gaussian Processes for Independence Tests with Non-iid Data in Causal Inference. ACM Trans. Intell. Syst. Technol. Seth R. Flaxman, Daniel B. Neill, Alexander J. Smola
2016	A	`conf`	Scalable Gaussian Processes for Characterizing Multidimensional Change Surfaces. AISTATS William Herlands, Andrew Gordon Wilson, Hannes Nickisch, Seth R. Flaxman, Daniel B. Neill, Wilbert Van Panhuis, Eric P. Xing
2016	J	`jnl`	Tucker Gaussian Process for Regression and Collaborative Filtering. CoRR Hyunjik Kim, Xiaoyu Lu, Seth R. Flaxman, Yee Whye Teh
2015	A*	`conf`	Fast Kronecker Inference in Gaussian Processes with non-Gaussian Likelihoods. ICML Seth R. Flaxman, Andrew Gordon Wilson, Daniel B. Neill, Hannes Nickisch, Alexander J. Smola
2015	A*	`conf`	Who Supported Obama in 2012?: Ecological Inference through Distribution Regression. KDD Seth R. Flaxman, Yu-Xiang Wang, Alexander J. Smola
2009	—	`conf`	Approximation Algorithms for Traffic Grooming in WDM Rings. ICC Kevin Corcoran, Seth R. Flaxman, Mark Neyer, Peter Scherpelz, Craig Weidert, Ran Libeskind-Hadas