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08/17/2023
Rethinking Hypothesis Tests
Null Hypothesis Significance Testing (NHST) have been a popular statisti...
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08/12/2023
Spectral smooth tests for goodness-of-fit
Goodness-of-fit tests are crucial tools for assessing the validity of st...
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05/12/2023
Expertise-based Weighting for Regression Models with Noisy Labels
Regression methods assume that accurate labels are available for trainin...
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04/20/2023
Is augmentation effective to improve prediction in imbalanced text datasets?
Imbalanced datasets present a significant challenge for machine learning...
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01/23/2023
Flexible conditional density estimation for time series
This paper introduces FlexCodeTS, a new conditional density estimator fo...
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11/11/2022
RFFNet: Scalable and interpretable kernel methods via Random Fourier Features
Kernel methods provide a flexible and theoretically grounded approach to...
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09/12/2022
Model interpretation using improved local regression with variable importance
A fundamental question on the use of ML models concerns the explanation ...
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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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05/17/2022
A unified framework for dataset shift diagnostics
Most machine learning (ML) methods assume that the data used in the trai...
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05/16/2022
The e-value and the Full Bayesian Significance Test: Logical Properties and Philosophical Consequences
This article gives a conceptual review of the e-value, ev(H|X) – the epi...
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04/04/2022
Logical coherence in Bayesian simultaneous three-way hypothesis tests
This paper studies whether Bayesian simultaneous three-way hypothesis te...
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02/18/2022
A new LDA formulation with covariates
The Latent Dirichlet Allocation (LDA) model is a popular method for crea...
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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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11/30/2021
Hierarchical clustering: visualization, feature importance and model selection
We propose methods for the analysis of hierarchical clustering that full...
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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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09/12/2020
MeLIME: Meaningful Local Explanation for Machine Learning Models
Most state-of-the-art machine learning algorithms induce black-box model...
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08/29/2020
Wisdom of the crowds forecasting the 2018 FIFA Men's World Cup
The FIFA Men's World Cup Tournament (WCT) is the most important football...
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07/24/2020
CD-split: efficient conformal regions in high dimensions
Conformal methods create prediction bands that control average coverage ...
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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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09/16/2019
Distance Assessment and Hypothesis Testing of High-Dimensional Samples using Variational Autoencoders
Given two distinct datasets, an important question is if they have arise...
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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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07/31/2019
Conditional independence testing: a predictive perspective
Conditional independence testing is a key problem required by many machi...
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07/31/2019
Local Interpretation Methods to Machine Learning Using the Domain of the Feature Space
As machine learning becomes an important part of many real world applica...
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06/24/2019
The NN-Stacking: Feature weighted linear stacking through neural networks
Stacking methods improve the prediction performance of regression models...
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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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05/19/2019
Teaching decision theory proof strategies using a crowdsourcing problem
Teaching how to derive minimax decision rules can be challenging because...
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04/13/2019
Interpretable hypothesis tests
Although hypothesis tests play a prominent role in Science, their interp...
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07/11/2018
Quantification under prior probability shift: the ratio estimator and its extensions
The quantification problem consists of determining the prevalence of a g...
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06/21/2018
WIKS: A general Bayesian nonparametric index for quantifying differences between two populations
The problem of deciding whether two samples arise from the same distribu...
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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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05/11/2018
Agnostic tests can control the type I and type II errors simultaneously
Despite its common practice, statistical hypothesis testing presents cha...
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02/01/2016
