Causalml: Python package for causal machine learning H Chen, T Harinen, JY Lee, M Yung, Z Zhao arXiv preprint arXiv:2002.11631, 2020 | 103 | 2020 |
Mutual manipulability and causal inbetweenness T Harinen Synthese 195, 35-54, 2018 | 57 | 2018 |
Uplift modeling for multiple treatments with cost optimization Z Zhao, T Harinen 2019 IEEE International Conference on Data Science and Advanced Analytics …, 2019 | 48 | 2019 |
Causal inference and machine learning in practice with econml and causalml: Industrial use cases at microsoft, tripadvisor, uber V Syrgkanis, G Lewis, M Oprescu, M Hei, K Battocchi, E Dillon, J Pan, ... Proceedings of the 27th ACM SIGKDD conference on knowledge discovery & data …, 2021 | 24 | 2021 |
Normal causes for normal effects: Reinvigorating the correspondence hypothesis about judgments of actual causation T Harinen Erkenntnis 82 (6), 1299-1320, 2017 | 10 | 2017 |
Feature selection methods for uplift modeling Z Zhao, Y Zhang, T Harinen, M Yung Computer Science, Mathematics (May 2020). https://arxiv. org/abs, 2005 | 6 | 2005 |
Causalml: Python package for causal machine learning, 2020 H Chen, T Harinen, JY Lee, M Yung, Z Zhao Cited on, 14, 2002 | 5 | 2002 |
Feature selection methods for uplift modeling and heterogeneous treatment effect Z Zhao, Y Zhang, T Harinen, M Yung IFIP International Conference on Artificial Intelligence Applications and …, 2022 | 4 | 2022 |
Causalml: Python package for causal machine learning. arXiv 2020 H Chen, T Harinen, J Lee, M Yung, Z Zhao arXiv preprint arXiv:2002.11631, 0 | 4 | |
Machine learning reveals how personalized climate communication can both succeed and backfire T Harinen, A Filipowicz, S Hakimi, R Iliev, M Klenk, E Sumner arXiv preprint arXiv:2109.05104, 2021 | 2 | 2021 |
System and method to infer thoughts and a process through which a human generated labels for a coding scheme YY Chen, S Hakimi, KM Lyons, Y Zhang, MK Hong, T Harinen, MP Van, ... US Patent App. 17/970,162, 2024 | | 2024 |
Systems and Methods Providing a ConjointNet Architecture for Enhanced Conjoint Analysis for Preference Prediction with Representation Learning Y Zhang, FR Chen, R Iliev, T Harinen, ALS Filipowicz, YY Chen, ... US Patent App. 18/113,937, 2023 | | 2023 |
Device and method for discovering causal patterns R Iliev, TH Harinen US Patent 11,847,127, 2023 | | 2023 |
System and method to detect and address overweight perceived by a subject in a salient situation YY Chen, T Harinen, DA Shamma, ES Sumner US Patent App. 17/581,731, 2023 | | 2023 |
Causal Inference and Machine Learning in Practice: Use Cases for Product, Brand, Policy and Beyond JY Lee, Y Wu, K Battocchi, F Vera, Z Zhao, T Harinen, J Pan, H Chen, ... Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023 | | 2023 |
Systems and methods for predicting the effect of an intervention via machine learning T Harinen US Patent App. 17/586,147, 2023 | | 2023 |
System and method for calculating generalized utilities and choice predictions TH Harinen, R Iliev, S Hakimi, ALS Filipowicz, ES Sumner US Patent App. 17/825,648, 2023 | | 2023 |
System and method for monitoring compromises in decision making YY Chen, TH Harinen, S Carter, R Iliev, Y Weng US Patent App. 17/465,612, 2023 | | 2023 |
Can Behavioral Experts Predict Outcome Heterogeneity? R Iliev, ALS Filipowicz, ES Sumner, F Chen, N Arechiga, S Carter, ... Proceedings of the Annual Meeting of the Cognitive Science Society 45 (45), 2023 | | 2023 |
Systems and methods for generating an interpretive behavioral model T Harinen, ALS Filipowicz, R Iliev, Y Zhang, K Lyons, CC Wu, YY Chen, ... US Patent App. 17/740,745, 2022 | | 2022 |