Nature

Time series causal relationships discovery through feature importance and ensemble models

Inferring causal relationships from observational data is a key challenge in understanding the interpretability of Machine Learning models. Given the ever-increasing amount of observational data ...
Times Higher Education

Research Engineer (Federated Causal Inference in Heterogeneous Data Environments) - UP

As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have the opportunity to be equipped with applied research skill sets that are ...
Nature

Dynamic decision making simulation with limited data via causal inference

The application of machine learning in decision-making has become widespread. However, investigating the impact of interventions in decision-making tasks poses significant challenges, particularly in ...
University of Bristol

Causal Inference in Epidemiology: Concepts and Methods

Many observational studies aim to make causal inferences about effects of interventions or exposures on health outcomes. This course defines causation, describes how emulating a ‘target trial’ can ...
BMJ

Causal inference in physical activity epidemiology research: an opportunity for better evidence

Decades of research have established a significant link between physical activity and health, influencing agenda setting, policy making and community awareness.1–4 However, the field continues to ...
lse

Causal Inference for Observational and Experimental Studies

This course is available on the MPhil/PhD in Economic Geography, MPhil/PhD in Environmental Economics, MPhil/PhD in International Relations, MPhil/PhD in Regional and Urban Planning Studies, MRes in ...
AlphaGalileo

Dermatology AI 2.0: Paradigm Shift to Causal Reasoning and Autonomous Care Transforms Skin Health

A comprehensive review published in Skin outlines the emergence of “Dermatology AI 2.0”, a fundamental transition from ...