Seth R. Flaxman

According to our database1, Seth R. Flaxman authored at least 18 papers between 2009 and 2020.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Other 

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Bibliography

2020
BART-based inference for Poisson processes.
CoRR, 2020

2019
Interpreting Deep Neural Networks Through Variable Importance.
CoRR, 2019

2018
Variational Learning on Aggregate Outputs with Gaussian Processes.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Multimodal Sentiment Analysis To Explore the Structure of Emotions.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Bayesian Approaches to Distribution Regression.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

AdaGeo: Adaptive Geometric Learning for Optimization and Sampling.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017
Bayesian Distribution Regression.
CoRR, 2017

European Union Regulations on Algorithmic Decision-Making and a "Right to Explanation".
AI Magazine, 2017

Feature-to-Feature Regression for a Two-Step Conditional Independence Test.
Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence, 2017

Poisson intensity estimation with reproducing kernels.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016
Gaussian Processes for Independence Tests with Non-iid Data in Causal Inference.
ACM Trans. Intell. Syst. Technol., 2016

Tucker Gaussian Process for Regression and Collaborative Filtering.
CoRR, 2016

EU regulations on algorithmic decision-making and a "right to explanation".
CoRR, 2016

Bayesian Learning of Kernel Embeddings.
Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence, 2016

Scalable Gaussian Processes for Characterizing Multidimensional Change Surfaces.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

2015
Who Supported Obama in 2012?: Ecological Inference through Distribution Regression.
Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

Fast Kronecker Inference in Gaussian Processes with non-Gaussian Likelihoods.
Proceedings of the 32nd International Conference on Machine Learning, 2015

2009
Approximation Algorithms for Traffic Grooming in WDM Rings.
Proceedings of IEEE International Conference on Communications, 2009


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