Green Silence: Double Machine Learning for Carbon Emissions Under Sample Selection Bias (pdf)
Green Silence: Double Machine Learning for Carbon Emissions Under Sample Selection Bias
-
- 0 Rating
- 0 Reviews
- 3 Students Enrolled
Green Silence: Double Machine Learning for Carbon Emissions Under Sample Selection Bias
Green Silence: Double Machine Learning for Carbon Emissions Under Sample Selection Bias
-
- 0 Rating
- 0 Reviews
- 3 Students Enrolled
Courselet Content
1 components
|
|
2.53 M |
Requirements
- Machine Learning
General Overview
Description
Green Silence: Double Machine Learning for
Carbon Emissions Under Sample Selection Bias
Courses that include this CL
Recommended for you
Meet the instructors !
About the Instructor
David Siang-Li Jheng is a PhD candidate at the Doctoral School of Cybernetics and Economic Statistics, Bucharest University of Economic Studies, Romania. His research focuses on detecting anomalies and modeling dependence structures in high-dimensional, high-frequency financial data.
With a background in financial engineering and mathematics from National Yang Ming Chiao Tung University (NYCU) and National Taiwan Normal University (NTNU), he investigates systemic risks through advanced methodologies such as Financial Risk Meters and anomaly detection models.