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6 papers · 1 filter
Outcome-wide longitudinal designs for causal inference: a new template for empirical studies
Tyler J. VanderWeele, Maya B. Mathur, Ying Chen
In this paper we propose a new template for empirical studies intended to assess causal effects: the outcome-wide longitudinal design. The approach is an extension of what is often…
The Influence of Numerical Error on an Inverse Problem Methodology in PDE Models
John T. Nardini, D. M. Bortz
The inverse problem methodology is a commonly-used framework in the sciences for parameter estimation and inference. It is typically performed by fitting a mathematical model to no…
Deciphering gene regulation from gene expression dynamics using deep neural network
Jingxiang Shen, Mariela D. Petkova, Yuhai Tu +2
Complex biological functions are carried out by the interaction of genes and proteins. Uncovering the gene regulation network behind a function is one of the central themes in biol…
Automatic Feature Selection in Markov State Models Using Genetic Algorithm
Qihua Chen, Jiangyan Feng, Shriyaa Mittal +1
Markov State Models (MSMs) are a powerful framework to reproduce the long-time conformational dynamics of biomolecules using a set of short Molecular Dynamics (MD) simulations. How…
The Theoretical Price of a Share-Based Payment with Performance Conditions and Implications for the Current Accounting Standards
Masahiro Fujimoto
Although the growth of share-based payments with performance conditions (hereafter, SPPC) is prominent today, the theoretical price of SPPC has not been sufficiently studied. Refle…
Technical Uncertainty in Real Options with Learning
Ali Al-Aradi, Alvaro Cartea, Sebastian Jaimungal
We introduce a new approach to incorporate uncertainty into the decision to invest in a commodity reserve. The investment is an irreversible one-off capital expenditure, after whic…