Large-Sample Bayesian Approximations for Privatized Data
This publication contributes to work in data privacy, applied statistics, with a focus reflected in its title: Large-Sample Bayesian …
Equivalence Testing Under Privacy Constraints
This publication contributes to work in data privacy, robust statistics, with a focus reflected in its title: Equivalence Testing Under …
Synthesizing the Counterfactual: A CTGAN-Augmented Causal Evaluation of Palliative Care on Spousal Depression
This publication contributes to work in applied statistics, with a focus reflected in its title: Synthesizing the Counterfactual: A …
Differentially Private Conformal Prediction via Quantile Binary Search
This publication contributes to work in data privacy, applied statistics, with a focus reflected in its title: Differentially Private …
Epigenetic Impact of Sleep Timing in Children: Novel DNA Methylation Signatures via SWAG Analysis
This publication contributes to work in applied statistics, model selection, with a focus reflected in its title: Epigenetic Impact of …
Fiducial Matching: Differentially Private Inference for Categorical Data
This publication contributes to work in data privacy, applied statistics, with a focus reflected in its title: Fiducial Matching: …
Machine Learning and Explainable AI for Type-2 Diabetes Management
This publication contributes to work in applied statistics, model selection, with a focus reflected in its title: Machine Learning and …
Interaction Between Climatic Variation and Pathogen Diversity Shape Endemic Disease Dynamics in the Agricultural Settings
This publication contributes to work in applied statistics, with a focus reflected in its title: Interaction Between Climatic Variation …
Form, Function, and Evolutionary Origins of Architectural Symmetry in Honey Bee Nests
This publication contributes to work in applied statistics, with a focus reflected in its title: Form, Function, and Evolutionary …
Inference for Large Scale Regression Models With Dependent Errors
This publication contributes to work in robust statistics, signal processing, with a focus reflected in its title: Inference for Large …
Stellar Blend Image Classification Using Computationally Efficient Gaussian Processes
This publication contributes to work in applied statistics, model selection, with a focus reflected in its title: Stellar Blend Image …
The Development and Characterization of a Next-Generation Oncolytic Virus Armed With an Anti-PD-1 sdAb for Osteosarcoma Treatment In Vitro
This publication contributes to work in applied statistics, with a focus reflected in its title: The Development and Characterization …
Wavelet Variance Based Robust Estimation of Composite Stochastic Models
This publication contributes to work in robust statistics, signal processing, with a focus reflected in its title: Wavelet Variance …
Artificial Neural Network-Empowered Projected Future Rainfall Intensity-Duration-Frequency Curves Under Changing Climate
This publication contributes to work in applied statistics, with a focus reflected in its title: Artificial Neural Network-Empowered …
Accounting for Vibration Noise in Stochastic Measurement Errors of Inertial Sensors
This publication contributes to work in signal processing, with a focus reflected in its title: Accounting for Vibration Noise in …
A Multi-Model Framework to Explore ADHD Diagnosis From Neuroimaging Data
This publication contributes to work in applied statistics, model selection, with a focus reflected in its title: A Multi-Model …
Accounting for Vibration Noise in Stochastic Measurement Errors
This publication contributes to work in signal processing, with a focus reflected in its title: Accounting for Vibration Noise in …
Stellar Blend Image Classification Using Computationally Efficient Gaussian Processes (MuyGPs)
This publication contributes to work in applied statistics, model selection, with a focus reflected in its title: Stellar Blend Image …
Robust and Scalable Inference for Stochastic Processes
This publication contributes to work in robust statistics, signal processing, with a focus reflected in its title: Robust and Scalable …
Winter Weather Predicts Honey Bee Colony Loss at the National Scale
This publication contributes to work in applied statistics, with a focus reflected in its title: Winter Weather Predicts Honey Bee …
Honey Bee Colony Loss Linked to Parasites, Pesticides and Extreme Weather Across the United States
This publication contributes to work in applied statistics, with a focus reflected in its title: Honey Bee Colony Loss Linked to …
Within-field variability in nutrients for site-specific agricultural management in irrigated cornfield
This work underlines how spatial variability in nutrients causes spatial variability in plant growth and crop yield across cornfields, …
Evidence of antagonistic predictive effects of miRNAs in breast cancer cohorts through data-driven networks
This work attempts to explain some contradictory results that have been found regarding the oncogenic or protective roles of miRNAs in …
Perturbed M-Estimation: A Further Investigation of Robust Statistics for Differential Privacy
This work highlights the links between statistical robustness and differential privacy, investigating a new method to protect data …
Multi-Signal Approaches for Repeated Sampling Schemes in Inertial Sensor Calibration
Sensor calibration is usually performed only on one error signal although calibration sessions often collect repeated samples. This …
Non applicability of validated predictive models for intensive care admission and death of COVID-19 patients in a secondary care hospital in Belgium
This study highlights how a highly-promoted predictive-score for admitting patients to intensive care is not applicable in Belgium …
Influence of Community-Led Total Sanitation and Water Coverages in the Control of Cholera in Madarounfa, Niger (2018)
Using a negative binomial hurdle model we provide evidence supporting the promotion of Community-Led Total Sanitation and Water …
Granger-causal testing for irregularly sampled time series with application to nitrogen signalling in Arabidopsis
This work puts forward an approach to test causal links between irregularly sampled signals with applications to nitrogen signalling …
Robust Two-Step Wavelet-Based Inference for Time Series Models
In this work we put forward a computationally efficient statistical procedure to estimate a wide range of time series models in a …
Chameleon microRNAs in Breast Cancer: Their Elusive Role as Regulatory Factors in Cancer Progression
This publication contributes to work in applied statistics, model selection, with a focus reflected in its title: Chameleon microRNAs …
Data of the Defense and the Defense of Data
An easy-to-read article highlighting the need and availability of solutions allowing the DoD to share more unclassified data with low …
Swag: A Wrapper Method for Sparse Learning
This publication contributes to work in applied statistics, model selection, with a focus reflected in its title: Swag: A Wrapper …
Wavelet-Based Moment-Matching Techniques for Inertial Sensor Calibration
This work compares current moment-matching techniques used to calibrate inertial sensors and identifies the optimal technique from a …
Using Survival Analysis to Predict Workers' Compensation Termination
This work studies the Californian worker’s compensation termination schemes and shows that the current schemes are inadequate and …
Multivariate Signal Modeling With Applications to Inertial Sensor Calibration
Low-cost inertial sensors are increasingly being used jointly in order to improve their navigation performance and this work provides a …
A Multisignal Wavelet Variance-Based Framework for Inertial Sensor Stochastic Error Modeling
This work combines the information from multiple signals to improve the estimation of stochastic model estimation for sensor …
Applied Time Series Analysis With R
This publication contributes to work in signal processing, with a focus reflected in its title: Applied Time Series Analysis With R.
Use of a New Online Calibration Platform With Applications to Inertial Sensors
This publication contributes to work in signal processing, with a focus reflected in its title: Use of a New Online Calibration …
Improved Stochastic Modelling of Low-Cost GNSS Receivers Positioning Errors
This publication contributes to work in signal processing, with a focus reflected in its title: Improved Stochastic Modelling of …
An Optimal Virtual Inertial Sensor Framework Using Wavelet Cross Covariance
This publication contributes to work in signal processing, with a focus reflected in its title: An Optimal Virtual Inertial Sensor …
A Two-Step Computationally Efficient Procedure for IMU Classification and Calibration
This publication contributes to work in applied statistics, signal processing, with a focus reflected in its title: A Two-Step …
Is Nonmetastatic Cutaneous Melanoma Predictable Through Genomic Biomarkers?
This publication contributes to work in applied statistics, model selection, with a focus reflected in its title: Is Nonmetastatic …
A Computationally Efficient Framework for Automatic Inertial Sensor Calibration
This paper introduces a robust, user-friendly R-based software platform using the generalized method of wavelet moments for efficient …
An Automatic Calibration Approach for the Stochastic Parameters of Inertial Sensors
This publication contributes to work in signal processing, with a focus reflected in its title: An Automatic Calibration Approach for …
A Computational Multivariate-Based Technique for Inertial Sensor Calibration
This publication contributes to work in signal processing, with a focus reflected in its title: A Computational Multivariate-Based …
A Study of the Allan Variance for Constant-Mean Nonstationary Processes
This work generalizes the theoretical form of Allan variance to include nonstationary processes, enabling more accurate interpretation …
An Overview of a New Sensor Calibration Platform
This publication contributes to work in signal processing, with a focus reflected in its title: An Overview of a New Sensor Calibration …
Wavelet-Based Improvements for Inertial Sensor Error Modeling
This paper enhances the Generalized Method of Wavelet Moments (GMWM) for parametric estimation of stochastic error signals by …
Wavelet Variance for Random Fields: An M-Estimation Framework
This publication contributes to work in robust statistics, signal processing, with a focus reflected in its title: Wavelet Variance for …
The gmwm R Package: A Comprehensive Tool for Time Series Analysis From State-Space Models to Robustness
This publication contributes to work in robust statistics, signal processing, with a focus reflected in its title: The gmwm R Package: …
On the Identifiability of Latent Models for Dependent Data
This publication contributes to work in model selection, signal processing, with a focus reflected in its title: On the Identifiability …
Fast and Robust Parametric Estimation for Time Series and Spatial Models
This publication contributes to work in robust statistics, signal processing, with a focus reflected in its title: Fast and Robust …
An R Package for Robust Time Series Analysis
This publication contributes to work in robust statistics, signal processing, with a focus reflected in its title: An R Package for …
A Predictive Based Regression Algorithm for Gene Network Selection
A new prediction-based objective function for gene selection is proposed, enabling the identification of small, interpretable models …
Discussion on Maximum Likelihood-Based Methods for Inertial Sensor Calibration
This work discusses issues with maximum likelihood identification of inertial sensor noise model parameters
Theoretical Limitations of Allan Variance-based Regression for Time Series Model Estimation
This work formally proves the statistical inconsistency of Allan variance-based parameter estimation for latent models, highlighting …
Robust Inference for Random Fields and Latent Models
This publication contributes to work in robust statistics, signal processing, with a focus reflected in its title: Robust Inference for …
Differentiating Inflammatory Bowel Diseases by Using Genomic Data: Dimension of the Problem and Network Organization
This publication contributes to work in applied statistics, model selection, with a focus reflected in its title: Differentiating …
Robust Inference for Time Series Models: A Wavelet-Based Framework
This publication contributes to work in robust statistics, signal processing, with a focus reflected in its title: Robust Inference for …
A Paradigmatic Regression Algorithm for Gene Selection Problems
This publication contributes to work in applied statistics, model selection, with a focus reflected in its title: A Paradigmatic …
An Inertial Sensor Calibration Platform to Estimate and Select Error Models
This publication contributes to work in applied statistics, signal processing, model selection, with a focus reflected in its title: An …
Automatic and Computationally Efficient Method for Model Selection in Inertial Sensor Calibration
This publication contributes to work in applied statistics, signal processing, model selection, with a focus reflected in its title: …
A Computationally Efficient Platform for Inertial Sensor Calibration
This publication contributes to work in applied statistics, signal processing, with a focus reflected in its title: A Computationally …
Automatic Identification and Calibration of Stochastic Parameters in Inertial Sensors
An algorithm based on the Generalized Method of Wavelet Moments (GMWM) is presented for identifying the nature and parameters of …
Beyond Allan Variance-GMWM Framework for Sensor Calibration
This publication contributes to work in signal processing, with a focus reflected in its title: Beyond Allan Variance-GMWM Framework …
Estimation of time series models via robust wavelet variance
A robust time series estimation method is proposed by enhancing the Generalized Method of Wavelet Moments (GMWM) with a robust …
Study of MEMS-Based Inertial Sensors Operating in Dynamic Conditions
This publication contributes to work in signal processing, with a focus reflected in its title: Study of MEMS-Based Inertial Sensors …
An Algorithm for Automatic Inertial Sensors Calibration
This publication contributes to work in applied statistics, signal processing, with a focus reflected in its title: An Algorithm for …
