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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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05/31/2022
Simulation-Based Inference with WALDO: Perfectly Calibrated Confidence Regions Using Any Prediction or Posterior Estimation Algorithm
The vast majority of modern machine learning targets prediction problems...
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05/29/2022
Calibrated Predictive Distributions via Diagnostics for Conditional Coverage
Uncertainty quantification is crucial for assessing the predictive abili...
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02/04/2022
Detecting Distributional Differences in Labeled Sequence Data with Application to Tropical Cyclone Satellite Imagery
Our goal is to quantify whether, and if so how, spatio-temporal patterns...
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09/24/2021
Identifying Distributional Differences in Convective Evolution Prior to Rapid Intensification in Tropical Cyclones
Tropical cyclone (TC) intensity forecasts are issued by human forecaster...
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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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12/30/2020
Spatio-temporal methods for estimating subsurface ocean thermal response to tropical cyclones
Prevailing theory contends that tropical cyclones (TCs) are primarily dr...
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10/09/2020
Wildfire Smoke and Air Quality: How Machine Learning Can Guide Forest Management
Prescribed burns are currently the most effective method of reducing the...
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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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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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11/25/2019
Unlocking GOES: A Statistical Framework for Quantifying the Evolution of Convective Structure in Tropical Cyclones
Tropical cyclones (TCs) rank among the most costly natural disasters in ...
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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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06/17/2019
(f)RFCDE: Random Forests for Conditional Density Estimation and Functional Data
Random forests is a common non-parametric regression technique which per...
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05/27/2019
Validation of Approximate Likelihood and Emulator Models for Computationally Intensive Simulations
Complex phenomena are often modeled with computationally intensive feed-...
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12/21/2018
Global and Local Two-Sample Tests via Regression
Two-sample testing is a fundamental problem in statistics. Despite its l...
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05/14/2018
ABC-CDE: Towards Approximate Bayesian Computation with Complex High-Dimensional Data and Limited Simulations
Approximate Bayesian Computation (ABC) is typically used when the likeli...
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04/16/2018
RFCDE: Random Forests for Conditional Density Estimation
Random forests is a common non-parametric regression technique which per...
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02/01/2016
