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Data Science in Science

@DataSciScience

OA journal publishing original research and reviews at the intersection of #Science & #DataScience. Affiliated journal of the American Statistical Association.

 New York
tandfonline.com/udss
Joined February 2021
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Great news! Data Science in Science has been accepted into Scopus! @tandfSTEM #Scopus #DataScience
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Data Science in Science retweeted
Data Science in Science (@DataSciScience) profile picture
Data Science in Science@DataSciScienceJul 3
Detecting Deforestation Using Robust Online Bayesian Monitoring tandfonline.com/doi/full/10.…
Detecting Deforestation Using Robust Online Bayesian Monitoring

Detecting Deforestation Using Robust Online Bayesian Monitoring

Near real time change detection is important for a variety of Earth monitoring applications and remains a high priority for remote sensing science. Data sparsity, subtle changes, seasonal trends, a...

tandfonline.com
3
243
Data Science in Science retweeted
Data Science in Science (@DataSciScience) profile picture
Data Science in Science@DataSciScienceJun 29
Predicting Atomistic Transitions with Transformers @tandfSTEM #MachineLearning #Data #Materials tandfonline.com/doi/full/10.…
Predicting Atomistic Transitions with Transformers

Predicting Atomistic Transitions with Transformers

Accurate knowledge of the atomistic transition pathways in materials and material surfaces is crucial for many material science problems. However, conventional simulation techniques used to find th...

tandfonline.com
3
1
273
Fast Line Integration of B-Spline Data Models tandfonline.com/doi/full/10.…
Fast Line Integration of B-Spline Data Models

Fast Line Integration of B-Spline Data Models

B-spline data models are a powerful way to represent scientific data sets with a functional approximation that admit analytical formulas for computing function values, derivatives, and box-aligned ...

tandfonline.com
1
1
217
Data Science in Science retweeted
Paul Naish (@PaulNaish78) profile picture
Paul Naish@PaulNaish78Sep 4
Election Day 2024: Exit Polling as a High-Impact Data Science Project to Engage Students in Civic Responsibility @tandfonline tandfonline.com/doi/full/10.…
Election Day 2024: Exit Polling as a High-Impact Data Science Project to Engage Students in Civic...

Election Day 2024: Exit Polling as a High-Impact Data Science Project to Engage Students in Civic...

This article shares a model for conducting a student-led exit polling project connected to American elections. The author, in his fall 2024 introductory data science course, enlisted his students t...

tandfonline.com
2
2
838
Data Science in Science retweeted
Data Science in Science (@DataSciScience) profile picture
Data Science in Science@DataSciScienceJun 22
Parameter Estimation and Seasonal Modification of the Fractional Poisson Process with Application to Vorticity Extremes over the North Atlantic tandfonline.com/doi/full/10.…
Parameter Estimation and Seasonal Modification of the Fractional Poisson Process with Application...

Parameter Estimation and Seasonal Modification of the Fractional Poisson Process with Application...

The fractional Poisson process (FPP) generalizes the standard Poisson process by replacing exponentially distributed return times with Mittag-Leffler distributed ones with an extra tail parameter, ...

tandfonline.com
2
1
246
Data Science in Science retweeted
Paul Naish (@PaulNaish78) profile picture
Paul Naish@PaulNaish78Jul 17
Multi-Modal Bayesian Neural Network Surrogates with Conjugate Last-Layer Estimation @DataSciScience tandfonline.com/doi/full/10.…
Multi-Modal Bayesian Neural Network Surrogates with Conjugate Last-Layer Estimation

Multi-Modal Bayesian Neural Network Surrogates with Conjugate Last-Layer Estimation

As data collection and simulation capabilities advance, multi-modal learning, the task of learning from multiple modalities and sources of data, is becoming an increasingly important area of resear...

tandfonline.com
2
3
395
Evaluating Missing Data Imputation Strategies for Environmental Mixture Models: A Simulation Study and Applied Analysis tandfonline.com/doi/full/10.…
Evaluating Missing Data Imputation Strategies for Environmental Mixture Models: A Simulation Study...

Evaluating Missing Data Imputation Strategies for Environmental Mixture Models: A Simulation Study...

Missing data are common in environmental mixture studies and can bias inference if not properly addressed. This study evaluates how different imputation strategies influence variable selection perf...

tandfonline.com
3
289
Data Science in Science retweeted
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Data Science in Science@DataSciScienceJun 19
Bayesian Deep Gaussian Processes for Correlated Functional Data: a Case Study in Cosmological Matter Power Spectra tandfonline.com/doi/full/10.…
Bayesian Deep Gaussian Processes for Correlated Functional Data: a Case Study in Cosmological...

Bayesian Deep Gaussian Processes for Correlated Functional Data: a Case Study in Cosmological...

Understanding the structure of our universe and the distribution of matter is an area of active research. As cosmological surveys grow in complexity, the development of emulators to efficiently and...

tandfonline.com
2
1
230
Detecting Deforestation Using Robust Online Bayesian Monitoring tandfonline.com/doi/full/10.…
Detecting Deforestation Using Robust Online Bayesian Monitoring

Detecting Deforestation Using Robust Online Bayesian Monitoring

Near real time change detection is important for a variety of Earth monitoring applications and remains a high priority for remote sensing science. Data sparsity, subtle changes, seasonal trends, a...

tandfonline.com
3
243
Predicting Atomistic Transitions with Transformers @tandfSTEM #MachineLearning #Data #Materials tandfonline.com/doi/full/10.…
Predicting Atomistic Transitions with Transformers

Predicting Atomistic Transitions with Transformers

Accurate knowledge of the atomistic transition pathways in materials and material surfaces is crucial for many material science problems. However, conventional simulation techniques used to find th...

tandfonline.com
3
1
273
Data Science in Science retweeted
Data Science in Science (@DataSciScience) profile picture
Data Science in Science@DataSciScienceJun 9
Predictions of Damages from Atlantic Tropical Cyclones in Two Scales: A Hierarchical Bayesian Study tandfonline.com/doi/full/10.…
Predictions of Damages from Atlantic Tropical Cyclones in Two Scales: A Hierarchical Bayesian Study

Predictions of Damages from Atlantic Tropical Cyclones in Two Scales: A Hierarchical Bayesian Study

We propose joint distributional models of tropical cyclone characteristics and the economic damages they inflict, using a hierarchical Bayesian framework. This is done in two temporal scales: (i) a...

tandfonline.com
2
258
Extreme temperatures on the Greenland ice sheet: a spatial model @tandfSTEM @tandfenviro #Greenland #SDG #Ice #ClimateChange #Statistics tandfonline.com/doi/full/10.…

Extreme temperatures on the Greenland ice sheet: a spatial model

Whilst surface ice melt from the Greenland ice sheet is one of the largest contributors to sea level rise, our understanding of this phenomenon arises mostly from case studies of specific melt even...

tandfonline.com
2
3
926
Parameter Estimation and Seasonal Modification of the Fractional Poisson Process with Application to Vorticity Extremes over the North Atlantic tandfonline.com/doi/full/10.…
Parameter Estimation and Seasonal Modification of the Fractional Poisson Process with Application...

Parameter Estimation and Seasonal Modification of the Fractional Poisson Process with Application...

The fractional Poisson process (FPP) generalizes the standard Poisson process by replacing exponentially distributed return times with Mittag-Leffler distributed ones with an extra tail parameter, ...

tandfonline.com
2
1
246
Bayesian Deep Gaussian Processes for Correlated Functional Data: a Case Study in Cosmological Matter Power Spectra tandfonline.com/doi/full/10.…
Bayesian Deep Gaussian Processes for Correlated Functional Data: a Case Study in Cosmological...

Bayesian Deep Gaussian Processes for Correlated Functional Data: a Case Study in Cosmological...

Understanding the structure of our universe and the distribution of matter is an area of active research. As cosmological surveys grow in complexity, the development of emulators to efficiently and...

tandfonline.com
2
1
230
Data Science in Science retweeted
Paul Naish (@PaulNaish78) profile picture
Paul Naish@PaulNaish78Jun 16
A Probabilistic Framework for Bias Correction and Fusion of Multi-Model Datasets @DataSciScience @tandfSTEM tandfonline.com/doi/full/10.…
A Probabilistic Framework for Bias Correction and Fusion of Multi-Model Datasets

A Probabilistic Framework for Bias Correction and Fusion of Multi-Model Datasets

Reliable outputs from physics-based models are essential for a wide range of scientific and operational applications, such as energy systems. However, physics-based numerical models often produce s...

tandfonline.com
1
213
Predictions of Damages from Atlantic Tropical Cyclones in Two Scales: A Hierarchical Bayesian Study tandfonline.com/doi/full/10.…
Predictions of Damages from Atlantic Tropical Cyclones in Two Scales: A Hierarchical Bayesian Study

Predictions of Damages from Atlantic Tropical Cyclones in Two Scales: A Hierarchical Bayesian Study

We propose joint distributional models of tropical cyclone characteristics and the economic damages they inflict, using a hierarchical Bayesian framework. This is done in two temporal scales: (i) a...

tandfonline.com
2
258
Data Science in Science retweeted
Data Science in Science (@DataSciScience) profile picture
Data Science in Science@DataSciScienceMay 13
An Efficient, Accurate, and Interpretable Machine Learning Method for Computing Probability of Failure @tandfSTEM tandfonline.com/doi/full/10.…
An Efficient, Accurate, and Interpretable Machine Learning Method for Computing Probability of...

An Efficient, Accurate, and Interpretable Machine Learning Method for Computing Probability of...

We introduce a novel machine learning method called the Penalized Profile Support Vector Machine based on the Gabriel edited set for the computation of the probability of failure for a complex syst...

tandfonline.com
3
4
387
Data Science in Science retweeted
Data Science in Science (@DataSciScience) profile picture
Data Science in Science@DataSciScience7 Apr 2025
Great news! Data Science in Science has been accepted into Scopus! @tandfSTEM #Scopus #DataScience
Image from Data Science in Science (@DataSciScience)
8
13
1,435
Data Science in Science retweeted
Paul Naish (@PaulNaish78) profile picture
Paul Naish@PaulNaish78May 15
Multi-Fidelity Bayesian Optimization with Gaussian Processes for Double Shell Inertial Confinement Fusion Target Design @DataSciScience @tandfSTEM tandfonline.com/doi/full/10.…
Multi-Fidelity Bayesian Optimization with Gaussian Processes for Double Shell Inertial Confinement...

Multi-Fidelity Bayesian Optimization with Gaussian Processes for Double Shell Inertial Confinement...

Reliable, secure access to energy is a major focus for national security efforts. One potential route to such energy is through fusion reactions in inertial confinement fusion (ICF) experiments. Su...

tandfonline.com
1
2
165
An Efficient, Accurate, and Interpretable Machine Learning Method for Computing Probability of Failure @tandfSTEM tandfonline.com/doi/full/10.…
An Efficient, Accurate, and Interpretable Machine Learning Method for Computing Probability of...

An Efficient, Accurate, and Interpretable Machine Learning Method for Computing Probability of...

We introduce a novel machine learning method called the Penalized Profile Support Vector Machine based on the Gabriel edited set for the computation of the probability of failure for a complex syst...

tandfonline.com
3
4
387
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