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08/25/2023
Nonparametric Additive Value Functions: Interpretable Reinforcement Learning with an Application to Surgical Recovery
We propose a nonparametric additive model for estimating interpretable v...
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01/21/2023
Scalable Gaussian Process Inference with Stan
Gaussian processes (GPs) are sophisticated distributions to model functi...
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01/12/2023
A Generalized Estimating Equation Approach to Network Regression
Regression models applied to network data where node attributes are the ...
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10/10/2022
Testing unit root non-stationarity in the presence of missing data in univariate time series of mobile health studies
The use of digital devices to collect data in mobile health (mHealth) st...
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07/15/2022
A 'one-size-fits-most' walking recognition method for smartphones, smartwatches, and wearable accelerometers
The ubiquity of personal digital devices offers unprecedented opportunit...
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06/29/2022
State space model multiple imputation for missing data in non-stationary multivariate time series with application in digital Psychiatry
Mobile technology enables unprecedented continuous monitoring of an indi...
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06/06/2022
Minimizing the Expected Posterior Entropy Yields Optimal Summary Statistics
Extracting low-dimensional summary statistics from large datasets is ess...
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09/02/2021
Combining Accelerometer and Gyroscope Data in Smartphone-Based Activity Recognition using Movelets
Objective: A patient's activity patterns can be informative about her/hi...
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06/16/2021
Maximum likelihood estimation for mechanistic network models
Mechanistic network models specify the mechanisms by which networks grow...
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02/19/2021
Inferring the minimum spanning tree from a sample network
Minimum spanning trees (MSTs) are used in a variety of fields, from comp...
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01/19/2021
Selection of Summary Statistics for Network Model Choice with Approximate Bayesian Computation
Approximate Bayesian Computation (ABC) now serves as one of the major st...
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11/09/2020
Scalable Approximate Bayesian Computation for Growing Network Models via Extrapolated and Sampled Summaries
Approximate Bayesian computation (ABC) is a simulation-based likelihood-...
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10/07/2019
A systematic review of human activity recognition using smartphones
Smartphones have become a global communication tool and more recently a ...
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03/20/2019
Activity Classification Using Smartphone Gyroscope and Accelerometer Data
Activities, such as walking and sitting, are commonly used in biomedical...
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03/18/2019
Efficient vaccination strategies for epidemic control using network information
Network-based interventions against epidemic spread are most powerful wh...
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06/28/2018
A Bootstrap Method for Goodness of Fit and Model Selection with a Single Observed Network
Network models are applied in numerous domains where data can be represe...
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05/29/2018
Connected but Segregated: Social Networks in Rural Villages
There is an increased appreciation for, and utilization of, social netwo...
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05/23/2018
Bayesian method for inferring the impact of geographical distance on intensity of communication
Both theoretical models and empirical findings suggest that the intensit...
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04/01/2018
Flexible Model Selection for Mechanistic Network Models via Super Learner
Application of network models can be found in many domains due to the va...
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12/19/2017
Generalizations of Edge Overlap to Weighted and Directed Networks
With the increasing availability of behavioral data from diverse digital...
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11/13/2017
ABCpy: A High-Performance Computing Perspective to Approximate Bayesian Computation
ABCpy is a highly modular scientific library for Approximate Bayesian Co...
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10/11/2017
The Social Bow Tie
Understanding tie strength in social networks, and the factors that infl...
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09/26/2017
Bayesian Inference of Spreading Processes on Networks
Infectious diseases are studied to understand their spreading mechanisms...
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09/26/2017