Data Science in Science

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

[Data Science in Science @DataSciScience]

Great news! Data Science in Science has been accepted into Scopus!

@tandfSTEM #Scopus #DataScience

[Data Science in Science @DataSciScience]

Detecting Deforestation Using Robust Online Bayesian Monitoring https://t.co/0qyTV6DO1G

[Data Science in Science @DataSciScience]

Predicting Atomistic Transitions with Transformers

@tandfSTEM #MachineLearning #Data #Materials
https://t.co/T2874Q0MaH

[Data Science in Science @DataSciScience]

Fast Line Integration of B-Spline Data Models https://t.co/P1yH7T6Zkb

[Paul Naish @PaulNaish78]

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

@tandfonline https://t.co/sIbhSZhit2

[Data Science in Science @DataSciScience]

Parameter Estimation and Seasonal Modification of the Fractional Poisson Process with Application to Vorticity Extremes over the North Atlantic https://t.co/Clv5LcjLMh

[Paul Naish @PaulNaish78]

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

@DataSciScience https://t.co/gM4yEun9uK

[Data Science in Science @DataSciScience]

Evaluating Missing Data Imputation Strategies for Environmental Mixture Models: A Simulation Study and Applied Analysis https://t.co/p46WIcv85s

[Data Science in Science @DataSciScience]

Bayesian Deep Gaussian Processes for Correlated Functional Data: a Case Study in Cosmological Matter Power Spectra https://t.co/o9uGMH4WHn

[Data Science in Science @DataSciScience]

Detecting Deforestation Using Robust Online Bayesian Monitoring https://t.co/0qyTV6DO1G

[Data Science in Science @DataSciScience]

Predicting Atomistic Transitions with Transformers

@tandfSTEM #MachineLearning #Data #Materials
https://t.co/T2874Q0MaH

[Data Science in Science @DataSciScience]

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

https://t.co/elHjlHd7MP

[Journal of Applied Statistics & JAS: Enviro Stats @JAppliedStats]

Extreme temperatures on the Greenland ice sheet: a spatial model

@tandfSTEM @tandfenviro #Greenland #SDG #Ice #ClimateChange #Statistics https://t.co/ZB4QGJLFVV

[Data Science in Science @DataSciScience]

Parameter Estimation and Seasonal Modification of the Fractional Poisson Process with Application to Vorticity Extremes over the North Atlantic https://t.co/Clv5LcjLMh

[Data Science in Science @DataSciScience]

Bayesian Deep Gaussian Processes for Correlated Functional Data: a Case Study in Cosmological Matter Power Spectra https://t.co/o9uGMH4WHn

[Paul Naish @PaulNaish78]

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

@DataSciScience @tandfSTEM https://t.co/xPyYVAkbzd

[Data Science in Science @DataSciScience]

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

https://t.co/elHjlHd7MP

[Data Science in Science @DataSciScience]

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

@tandfSTEM https://t.co/0BMWqBz0kH

[Data Science in Science @DataSciScience]

Great news! Data Science in Science has been accepted into Scopus!

@tandfSTEM #Scopus #DataScience

[Paul Naish @PaulNaish78]

Multi-Fidelity Bayesian Optimization with Gaussian Processes for Double Shell Inertial Confinement Fusion Target Design

@DataSciScience @tandfSTEM https://t.co/9X2GB5un6S

[Data Science in Science @DataSciScience]

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

@tandfSTEM https://t.co/0BMWqBz0kH