Generalized Random Forests

5 October 2016

Papers citing "Generalized Random Forests"

50 / 86 papers shown

Title
Improving Random Forests by Smoothing Ziyi Liu Phuc Luong Mario Boley Daniel F. Schmidt UQCV 37 0 0 11 May 2025
CAST: Time-Varying Treatment Effects with Application to Chemotherapy and Radiotherapy on Head and Neck Squamous Cell Carcinoma Everest Yang Ria Vasishtha Luqman K. Dad Lisa A. Kachnic Andrew Hope Eric Wang Xiao Wu Yading Yuan David J. Brenner Igor Shuryak CML 21 0 0 09 May 2025
Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling David Svensson Erik Hermansson N. Nikolaou Konstantinos Sechidis Ilya Lipkovich CML 51 0 0 02 May 2025
Pre-Training Estimators for Structural Models: Application to Consumer Search Yanhao 'Max' Wei Zhenling Jiang 31 0 0 01 May 2025
Consistent Causal Inference of Group Effects in Non-Targeted Trials with Finitely Many Effect Levels Georgios Mavroudeas M. Magdon-Ismail Kristin P. Bennett Jason Kuruzovich 24 0 0 22 Apr 2025
A New Transformation Approach for Uplift Modeling with Binary Outcome Kun Li Jiang Tian 34 0 0 10 Jan 2025
Double Machine Learning for Static Panel Models with Fixed Effects Paul Clarke Annalivia Polselli 52 2 0 03 Jan 2025
Causality Pursuit from Heterogeneous Environments via Neural Adversarial Invariance Learning Yihong Gu Cong Fang Peter Bühlmann Jianqing Fan CML OOD 70 2 0 31 Dec 2024
Segment Discovery: Enhancing E-commerce Targeting Qiqi Li Roopali Singh Charin Polpanumas Tanner Fiez Namita Kumar Shreya Chakrabarti 35 1 0 31 Dec 2024
Distilling interpretable causal trees from causal forests Patrick Rehill CML 28 0 0 02 Aug 2024
Humas: A Heterogeneity- and Upgrade-aware Microservice Auto-scaling Framework in Large-scale Data Centers Qin Hua Dingyu Yang Shiyou Qian Jian Cao Guangtao Xue Minglu Li 34 1 0 22 Jun 2024
C-Learner: Constrained Learning for Causal Inference and Semiparametric Statistics T. Cai Yuri Fonseca Kaiwen Hou Hongseok Namkoong CML 25 1 0 15 May 2024
Differentiable Pareto-Smoothed Weighting for High-Dimensional Heterogeneous Treatment Effect Estimation Yoichi Chikahara Kansei Ushiyama 29 0 0 26 Apr 2024
Triple/Debiased Lasso for Statistical Inference of Conditional Average Treatment Effects Masahiro Kato CML 34 1 0 05 Mar 2024
Structure-agnostic Optimality of Doubly Robust Learning for Treatment Effect Estimation Jikai Jin Vasilis Syrgkanis CML 67 1 0 22 Feb 2024
Extrapolation-Aware Nonparametric Statistical Inference Niklas Pfister Peter Buhlmann 21 4 0 15 Feb 2024
Instrumental Variable Estimation for Causal Inference in Longitudinal Data with Time-Dependent Latent Confounders Debo Cheng Ziqi Xu Jiuyong Li Lin Liu Jixue Liu Wentao Gao T. Le CML 36 6 0 12 Dec 2023
The impact of heteroskedasticity on uplift modeling B. Bokelmann Stefan Lessmann 21 0 0 08 Dec 2023
Causal Dynamic Variational Autoencoder for Counterfactual Regression in Longitudinal Data Mouad El Bouchattaoui Myriam Tami Benoit Lepetit P. Cournède CML OOD 58 2 0 16 Oct 2023
A Semiparametric Instrumented Difference-in-Differences Approach to Policy Learning Pan Zhao Yifan Cui CML 26 1 0 14 Oct 2023
Model-free selective inference under covariate shift via weighted conformal p-values Ying Jin Emmanuel J. Candès 23 15 0 18 Jul 2023
Should I Stop or Should I Go: Early Stopping with Heterogeneous Populations Hammaad Adam Fan Yin Huibin Mary Hu Neil A. Tenenholtz Lorin Crawford Lester W. Mackey Allison Koenecke 22 1 0 20 Jun 2023
Maximally Machine-Learnable Portfolios Philippe Goulet Coulombe Maximilian Göbel 21 3 0 08 Jun 2023
Data-OOB: Out-of-bag Estimate as a Simple and Efficient Data Value Yongchan Kwon James Y. Zou TDI FedML 31 35 0 16 Apr 2023
Linking a predictive model to causal effect estimation Jiuyong Li Lin Liu Ziqi Xu Ha Xuan Tran T. Le Jixue Liu CML 20 0 0 10 Apr 2023
A new methodology to predict the oncotype scores based on clinico-pathological data with similar tumor profiles Z. A. Masry Romain Pic Clément Dombry Chrisine Devalland 19 6 0 13 Mar 2023
Confidence and Uncertainty Assessment for Distributional Random Forests Jeffrey Näf Corinne Emmenegger Peter Buhlmann N. Meinshausen 30 3 0 11 Feb 2023
Causal Inference Based Single-branch Ensemble Trees For Uplift Modeling Fanglan Zheng Menghan Wang Kun Li Jiang Tian Xiaojia Xiang CML 18 0 0 03 Feb 2023
How to select predictive models for causal inference? M. Doutreligne Gaël Varoquaux ELM CML 21 2 0 01 Feb 2023
Proximal Causal Learning of Conditional Average Treatment Effects Erik Sverdrup Yifan Cui CML 21 4 0 26 Jan 2023
Data-Driven Estimation of Heterogeneous Treatment Effects Christopher Tran Keith Burghardt Kristina Lerman Elena Zheleva CML 25 1 0 16 Jan 2023
Debiased machine learning for estimating the causal effect of urban traffic on pedestrian crossing behaviour K. Kamal Bilal Farooq 33 3 0 21 Dec 2022
Criteria for Classifying Forecasting Methods Tim Januschowski Jan Gasthaus Bernie Wang David Salinas Valentin Flunkert Michael Bohlke-Schneider Laurent Callot AI4TS 21 173 0 07 Dec 2022
A Double Machine Learning Trend Model for Citizen Science Data Daniel Fink A. Johnston Matthew Strimas‐Mackey T. Auer W. Hochachka ... Lauren Oldham Jaromczyk O. Robinson Christopher Wood S. Kelling A. Rodewald 18 15 0 27 Oct 2022
Positive-Unlabeled Learning using Random Forests via Recursive Greedy Risk Minimization Jo Wilton Abigail M. Y. Koay R. Ko Miao Xu N. Ye 13 13 0 16 Oct 2022
Falsification before Extrapolation in Causal Effect Estimation Zeshan Hussain Michael Oberst M. Shih David Sontag CML 39 8 0 27 Sep 2022
Stochastic Tree Ensembles for Estimating Heterogeneous Effects Nikolay M. Krantsevich Jingyu He P. R. Hahn CML 27 13 0 15 Sep 2022
The Infinitesimal Jackknife and Combinations of Models Indrayudh Ghosal Yunzhe Zhou Giles Hooker 28 4 0 31 Aug 2022
A Recursive Partitioning Approach for Dynamic Discrete Choice Modeling in High Dimensional Settings E. Barzegary Hema Yoganarasimhan 13 0 0 02 Aug 2022
FACT: High-Dimensional Random Forests Inference Chien-Ming Chi Yingying Fan Jinchi Lv 27 2 0 04 Jul 2022
What Makes Forest-Based Heterogeneous Treatment Effect Estimators Work? Susanne Dandl Torsten Hothorn H. Seibold Erik Sverdrup Stefan Wager A. Zeileis CML 34 11 0 21 Jun 2022
A review of machine learning concepts and methods for addressing challenges in probabilistic hydrological post-processing and forecasting Georgia Papacharalampous Hristos Tyralis AI4CE 27 28 0 17 Jun 2022
Benchmarking Heterogeneous Treatment Effect Models through the Lens of Interpretability Jonathan Crabbé Alicia Curth Ioana Bica M. Schaar CML 20 15 0 16 Jun 2022
Image-based Treatment Effect Heterogeneity Connor Jerzak Fredrik D. Johansson Adel Daoud 24 20 0 13 Jun 2022
Efficient Heterogeneous Treatment Effect Estimation With Multiple Experiments and Multiple Outcomes Leon Yao Caroline Lo Israel Nir S. Tan Ariel Evnine Adam Lerer A. Peysakhovich CML 21 6 0 10 Jun 2022
Discovering Ancestral Instrumental Variables for Causal Inference from Observational Data Debo Cheng Jiuyong Li Lin Liu Kui Yu Thuc Duy Lee Hefei University of Technology CML 14 13 0 04 Jun 2022
Robust and Agnostic Learning of Conditional Distributional Treatment Effects Nathan Kallus M. Oprescu CML OOD 35 10 0 23 May 2022
Neuroevolutionary Feature Representations for Causal Inference Michael C. Burkhart Gabriel Ruiz CML OOD 16 2 0 21 May 2022
Flexible Modeling and Multitask Learning using Differentiable Tree Ensembles Shibal Ibrahim Hussein Hazimeh Rahul Mazumder 34 4 0 19 May 2022
Towards assessing agricultural land suitability with causal machine learning Georgios Giannarakis Vasileios Sitokonstantinou R. Lorilla C. Kontoes CML 18 20 0 27 Apr 2022