46 citations · 46 across the 2 of their papers we have counts for
3 papers
cs.LG2021
Machine learning reveals how personalized climate communication can both succeed and backfire
Totte Harinen, Alexandre Filipowicz, Shabnam Hakimi +3
Different advertising messages work for different people. Machine learning can be an effective way to personalise climate communications. In this paper we use machine learning to r…
cs.CY2020★ 46 cited
CausalML: Python Package for Causal Machine Learning
Huigang Chen, Totte Harinen, Jeong-Yoon Lee +2
CausalML is a Python implementation of algorithms related to causal inference and machine learning. Algorithms combining causal inference and machine learning have been a trending…
stat.ML2019
Uplift Modeling for Multiple Treatments with Cost Optimization
Zhenyu Zhao, Totte Harinen
Uplift modeling is an emerging machine learning approach for estimating the treatment effect at an individual or subgroup level. It can be used for optimizing the performance of in…