A machine-learning method predicts whether a genetic variant is pathogenic and affects certain human tissues. The ...

In complex systems, a significant challenge is to quantify emergent phenomena through data-driven methods. In a recent ...

To increase the robustness to weak labels, we first adjust the classification margin of negative labels using the label causality matrix, which is constructed by the conditional probability of label ...

With summarized data from publicly available genome-wide association studies (GWASs), a two-sample Mendelian randomization (TSMR) analysis is conducted on the causality between the exposure and the ...

Python version is here) This toolbox includes several functional connectome measures, such as VARDNN-DI, VARDNN-GC, VARLSTM-GC, multivariate Granger Causality (GC), pairwise ... then show output of ...

DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical ...

Al-Daghistani, Sami 2022. The Foundation of Norms in Islamic Jurisprudence and Theology By Omar Farahat. Cambridge: Cambridge University Press, 2019. Pp. 256. $99.99 (cloth); $80.00 (digital). ISBN: ...

Check if you have access via personal or institutional login This book, geared toward academic researchers and graduate students, brings together research on all facets of how time and causality ...

Here, we provide an accessible and critical review of three statistical causal discovery approaches (pairwise correlation, Granger causality, and state space reconstruction), using examples inspired ...

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