Itai Dattner
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View article: Compensation for Matrix Effects in High-Dimensional Spectral Data Using Standard Addition
Compensation for Matrix Effects in High-Dimensional Spectral Data Using Standard Addition Open
The standard addition method is widely used in analytical chemistry to compensate for matrix effects. While effective with single signals (e.g., absorbance at a single wavelength) and independent of matrix composition or blank measurements…
View article: Model Selection for Ordinary Differential Equations: A Statistical Testing Approach
Model Selection for Ordinary Differential Equations: A Statistical Testing Approach Open
Ordinary differential equations (ODEs) are foundational tools in modeling intricate dynamics across a gamut of scientific disciplines. Yet, a possibility to represent a single phenomenon through multiple ODE models, driven by different und…
View article: Adaptive Physics-Guided Neural Network
Adaptive Physics-Guided Neural Network Open
This paper introduces an adaptive physics-guided neural network (APGNN) framework for predicting quality attributes from image data by integrating physical laws into deep learning models. The APGNN adaptively balances data-driven and physi…
View article: Physics-Guided Inverse Regression for Crop Quality Assessment
Physics-Guided Inverse Regression for Crop Quality Assessment Open
We present an innovative approach leveraging Physics-Guided Neural Networks (PGNNs) for enhancing agricultural quality assessments. Central to our methodology is the application of physics-guided inverse regression, a technique that signif…
View article: Modelling motion energy in psychotherapy: A dynamical systems approach
Modelling motion energy in psychotherapy: A dynamical systems approach Open
In this study we introduce an innovative mathematical and statistical framework for the analysis of motion energy dynamics in psychotherapy sessions. Our method combines motion energy dynamics with coupled linear ordinary differential equa…
View article: Physics-Guided Inverse Regression for Crop Quality Assessment
Physics-Guided Inverse Regression for Crop Quality Assessment Open
We present an innovative approach leveraging Physics-Guided Neural Networks (PGNNs) for enhancing agricultural quality assessments. Central to our methodology is the application of physics-guided inverse regression, a technique that signif…
View article: Expectation-Updating: Understanding the Dynamics of Expectancy in Psychotherapy for Depression
Expectation-Updating: Understanding the Dynamics of Expectancy in Psychotherapy for Depression Open
Background: In psychotherapy, patients’ expectations from treatment, i.e., expectancy, are associated with treatment success. The current study introduces the concept of expectancy updating, the dynamics of expectancy during the psychother…
View article: Model Selection for Ordinary Differential Equations: a Statistical Testing Approach
Model Selection for Ordinary Differential Equations: a Statistical Testing Approach Open
Ordinary differential equations (ODEs) are foundational in modeling intricate dynamics across a gamut of scientific disciplines. Yet, a possibility to represent a single phenomenon through multiple ODE models, driven by different understan…
View article: Modeling Motion Dynamics in Psychotherapy: a Dynamical Systems Approach
Modeling Motion Dynamics in Psychotherapy: a Dynamical Systems Approach Open
This study introduces a novel mechanistic modeling and statistical framework for analyzing motion energy dynamics within psychotherapy sessions. We transform raw motion energy data into an interpretable narrative of therapist-patient inter…
View article: Digital twins and the future of precision mental health
Digital twins and the future of precision mental health Open
Science faces challenges in developing much-needed precision mental health treatments to accurately identify and diagnose mental health problems and the optimal treatment for each individual. Digital twins (DTs) promise to revolutionize th…
View article: A Robust Server-Effort Policy for Fluid Processing Networks
A Robust Server-Effort Policy for Fluid Processing Networks Open
Multi-Class Processing Networks describe a set of servers that perform multiple classes of jobs on different items. A useful and tractable way to find an optimal control for such a network is to approximate it by a fluid model, resulting i…
View article: The role of statisticians in the response to COVID-19 in Israel: a holistic point of view
The role of statisticians in the response to COVID-19 in Israel: a holistic point of view Open
The COVID-19 pandemic cast a dramatic spotlight on the use of data as a fundamental component of good decision-making. Evaluating and comparing alternative policies required information on concurrent infection rates and insightful analysis…
View article: The role of children in the spread of COVID-19: Using household data from Bnei Brak, Israel, to estimate the relative susceptibility and infectivity of children
The role of children in the spread of COVID-19: Using household data from Bnei Brak, Israel, to estimate the relative susceptibility and infectivity of children Open
One of the significant unanswered questions about COVID-19 epidemiology relates to the role of children in transmission. This study uses data on infections within households in order to estimate the susceptibility and infectivity of childr…
View article: The role of children in the spread of COVID-19: Using household data from Bnei Brak, Israel, to estimate the relative susceptibility and infectivity of children
The role of children in the spread of COVID-19: Using household data from Bnei Brak, Israel, to estimate the relative susceptibility and infectivity of children Open
Summary Background One of the significant unanswered questions about COVID-19 epidemiology relates to the role of children in transmission. In this study we estimate susceptibility and infectivity of children compared to those of adults. U…
View article: Separable Nonlinear Least-Squares Parameter Estimation for Complex Dynamic Systems
Separable Nonlinear Least-Squares Parameter Estimation for Complex Dynamic Systems Open
Nonlinear dynamic models are widely used for characterizing processes that govern complex biological pathway systems. Over the past decade, validation and further development of these models became possible due to data collected via high-t…
View article: simode: R Package for Statistical Inference of Ordinary Differential Equations using Separable Integral-Matching
simode: R Package for Statistical Inference of Ordinary Differential Equations using Separable Integral-Matching Open
Yaari et al., (2019). simode: R Package for Statistical Inference of Ordinary Differential Equations using Separable Integral-Matching. Journal of Open Source Software, 4(44), 1850, https://doi.org/10.21105/joss.01850
View article: Separable nonlinear least-squares parameter estimation for complex dynamic systems
Separable nonlinear least-squares parameter estimation for complex dynamic systems Open
Nonlinear dynamic models are widely used for characterizing functional forms of processes that govern complex biological pathway systems. Over the past decade, validation and further development of these models became possible due to data …
View article: How many groups? A statistical methodology for data-driven partitioning of infectious disease incidence into age-groups
How many groups? A statistical methodology for data-driven partitioning of infectious disease incidence into age-groups Open
Understanding age-group dynamics of infectious diseases is a fundamental issue for both scientific study and policymaking. Age-structure epidemic models were developed in order to study and improve our understanding of these dynamics. By f…
View article: A statistical methodology for data-driven partitioning of infectious disease incidence into age-groups
A statistical methodology for data-driven partitioning of infectious disease incidence into age-groups Open
Understanding age-group dynamics of infectious diseases is a fundamental issue for both scientific study and policymaking. Age-structure epidemic models were developed in order to study and improve our understanding of these dynamics. By f…
View article: simode: R Package for statistical inference of ordinary differential equations using separable integral-matching
simode: R Package for statistical inference of ordinary differential equations using separable integral-matching Open
In this paper we describe simode: Separable Integral Matching for Ordinary Differential Equations. The statistical methodologies applied in the package focus on several minimization procedures of an integral-matching criterion function, ta…
View article: A Guided FP-growth algorithm for multitude-targeted mining of big data
A Guided FP-growth algorithm for multitude-targeted mining of big data Open
In this paper we present the GFP-growth (Guided FP-growth) algorithm, a novel method for multitude-targeted mining: finding the count of a given large list of itemsets in large data. The GFP-growth algorithm is designed to focus on the spe…
View article: A two-stage approach for estimating the parameters of an age-group epidemic model from incidence data
A two-stage approach for estimating the parameters of an age-group epidemic model from incidence data Open
Age-dependent dynamics is an important characteristic of many infectious diseases. Age-group epidemic models describe the infection dynamics in different age-groups by allowing to set distinct parameter values for each. However, such model…
View article: Modelling and parameter inference of predator–prey dynamics in heterogeneous environments using the direct integral approach
Modelling and parameter inference of predator–prey dynamics in heterogeneous environments using the direct integral approach Open
Most bacterial habitats are topographically complex in the micro scale. Important examples include the gastrointestinal and tracheal tracts, and the soil. Although there are myriad theoretical studies that explore the role of spatial struc…
View article: Consistency of direct integral estimator for partially observed systems of ordinary differential equations linear in the parameters
Consistency of direct integral estimator for partially observed systems of ordinary differential equations linear in the parameters Open
Dynamic systems are ubiquitous in nature and are used to model many processes in biology, chemistry, physics, medicine, and engineering. In particular, systems of ordinary differential equations are commonly used for the mathematical model…
View article: Supplementary material from "Modelling and parameter inference of predator–prey dynamics in heterogeneous environments using the direct integral approach"
Supplementary material from "Modelling and parameter inference of predator–prey dynamics in heterogeneous environments using the direct integral approach" Open
Most bacterial habitats are topographically complex in the micro scale. Important examples include the gastrointestinal and tracheal tracts, and the soil. Although there are myriad theoretical studies that explore the role of spatial struc…
View article: A Model-Based Initial Guess for Estimating Parameters in Systems of Ordinary Differential Equations
A Model-Based Initial Guess for Estimating Parameters in Systems of Ordinary Differential Equations Open
Summary The inverse problem of parameter estimation from noisy observations is a major challenge in statistical inference for dynamical systems. Parameter estimation is usually carried out by optimizing some criterion function over the par…
View article: Accelerated least squares estimation for systems of ordinary differential equations
Accelerated least squares estimation for systems of ordinary differential equations Open
We study the problem of parameter estimation for a system of ordinary differential equations based on noisy observations on the solution of the system. A classical estimation approach to this problem is the least squares method. Owing to a…
View article: Optimal rate of direct estimators in systems of ordinary differential equations linear in functions of the parameters
Optimal rate of direct estimators in systems of ordinary differential equations linear in functions of the parameters Open
Many processes in biology, chemistry, physics, medicine, and engineering are modeled by a system of differential equations. Such a system is usually characterized via unknown parameters and estimating their ‘true’ value is thus required. I…