Philosophy and the practice of Bayesian statistics
A Gelman, CR Shalizi - British Journal of Mathematical and …, 2013 - Wiley Online Library
A substantial school in the philosophy of science identifies Bayesian inference with inductive
inference and even rationality as such, and seems to be strengthened by the rise and …
inference and even rationality as such, and seems to be strengthened by the rise and …
Biosystems design by machine learning
Biosystems such as enzymes, pathways, and whole cells have been increasingly explored
for biotechnological applications. However, the intricate connectivity and resulting …
for biotechnological applications. However, the intricate connectivity and resulting …
Prediction of surface chloride concentration of marine concrete using ensemble machine learning
This paper develops and employs an ensemble machine learning (ML) model for prediction
of surface chloride concentration (C s) of concrete, which is an essential parameter for …
of surface chloride concentration (C s) of concrete, which is an essential parameter for …
Offloading optimization in edge computing for deep-learning-enabled target tracking by internet of UAVs
The empowering unmanned aerial vehicles (UAVs) have been extensively used in providing
intelligence such as target tracking. In our field experiments, a pretrained convolutional …
intelligence such as target tracking. In our field experiments, a pretrained convolutional …
An ensemble machine learning approach for prediction and optimization of modulus of elasticity of recycled aggregate concrete
This paper presents an ensemble machine learning (ML) model for prediction of modulus of
elasticity (MOE) of concrete formulated using recycled concrete aggregate (RCA), in relation …
elasticity (MOE) of concrete formulated using recycled concrete aggregate (RCA), in relation …
[HTML][HTML] A comparison of machine learning methods for ozone pollution prediction
Precise and efficient ozone (O 3) concentration prediction is crucial for weather monitoring
and environmental policymaking due to the harmful effects of high O 3 pollution levels on …
and environmental policymaking due to the harmful effects of high O 3 pollution levels on …
Daily streamflow forecasting by machine learning methods with weather and climate inputs
Weather forecast data generated by the NOAA Global Forecasting System (GFS) model,
climate indices, and local meteo-hydrologic observations were used to forecast daily …
climate indices, and local meteo-hydrologic observations were used to forecast daily …
[HTML][HTML] Studying depression using imaging and machine learning methods
MJ Patel, A Khalaf, HJ Aizenstein - NeuroImage: Clinical, 2016 - Elsevier
Depression is a complex clinical entity that can pose challenges for clinicians regarding both
accurate diagnosis and effective timely treatment. These challenges have prompted the …
accurate diagnosis and effective timely treatment. These challenges have prompted the …
Characterization of the equivalence of robustification and regularization in linear and matrix regression
D Bertsimas, MS Copenhaver - European Journal of Operational Research, 2018 - Elsevier
The notion of developing statistical methods in machine learning which are robust to
adversarial perturbations in the underlying data has been the subject of increasing interest …
adversarial perturbations in the underlying data has been the subject of increasing interest …
Bagging and multilayer perceptron hybrid intelligence models predicting the swelling potential of soil
DD Nguyen, PC Roussis, BT Pham… - Transportation …, 2022 - Elsevier
Seasonal variations of the moisture content of fine-grained soils may result in the
accumulation of significant volumetric strains, which may affect the stability of geotechnical …
accumulation of significant volumetric strains, which may affect the stability of geotechnical …