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06/12/2023
Deep Gaussian Mixture Ensembles
This work introduces a novel probabilistic deep learning technique calle...
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12/12/2022
Fast Learning of Multidimensional Hawkes Processes via Frank-Wolfe
Hawkes processes have recently risen to the forefront of tools when it c...
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08/16/2022
Online Learning for Mixture of Multivariate Hawkes Processes
Online learning of Hawkes processes has received increasing attention in...
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07/27/2022
Differentially Private Learning of Hawkes Processes
Hawkes processes have recently gained increasing attention from the mach...
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05/31/2022
Structural Forecasting for Short-term Tropical Cyclone Intensity Guidance
Geostationary satellite (GOES) imagery provides a high temporal resoluti...
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02/10/2022
Fair When Trained, Unfair When Deployed: Observable Fairness Measures are Unstable in Performative Prediction Settings
Many popular algorithmic fairness measures depend on the joint distribut...
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07/08/2021
Likelihood-Free Frequentist Inference: Bridging Classical Statistics and Machine Learning in Simulation and Uncertainty Quantification
Many areas of science make extensive use of computer simulators that imp...
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02/20/2021
Validating Conditional Density Models and Bayesian Inference Algorithms
Conditional density models f(y|x), where x represents a potentially high...
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10/08/2020
HECT: High-Dimensional Ensemble Consistency Testing for Climate Models
Climate models play a crucial role in understanding the effect of enviro...
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10/07/2020
Structural Forecasting for Tropical Cyclone Intensity Prediction: Providing Insight with Deep Learning
Tropical cyclone (TC) intensity forecasts are ultimately issued by human...
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03/01/2020
Architectural Distant Reading Using Machine Learning to Identify Typological Traits Across Multiple Buildings
This paper introduces an approach to architectural “distant reading”: th...
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03/01/2020
When the Oracle Misleads: Modeling the Consequences of Using Observable Rather than Potential Outcomes in Risk Assessment Instruments
Machine learning-based Risk Assessment Instruments are increasingly wide...
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03/01/2020
Clarifying the Hubble constant tension with a Bayesian hierarchical model of the local distance ladder
Estimates of the Hubble constant, $H_0$, from the local distance ladder ...
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03/01/2020
Lebesgue Regression
We propose Lebesgue Regression, a non-parametric high-dimensional regres...
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03/01/2020
Feature Engineering for Entity Resolution with Arabic Names: Improving Estimates of Observed Casualties in the Syrian Civil War
Entity resolution or record linkage is the task of identifying records r...
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03/01/2020
Predictive Inference of a Wildfire Risk Pipeline in the United States
Wildfires are rare catastrophic events that are influenced by global cli...
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02/24/2020
Confidence Sets and Hypothesis Testing in a Likelihood-Free Inference Setting
Parameter estimation, statistical tests and confidence sets are the corn...
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08/30/2019
Conditional Density Estimation Tools in Python and R with Applications to Photometric Redshifts and Likelihood-Free Cosmological Inference
It is well known in astronomy that propagating non-Gaussian prediction u...
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06/20/2019
A Flexible Pipeline for Prediction of Tropical Cyclone Paths
Hurricanes and, more generally, tropical cyclones (TCs) are rare, comple...
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05/27/2019
