Communities
Connect sessions
AI calendar
Organizations
Join Slack
Contact Sales
Search
Open menu
Home
Papers
1707.02641
Cited By
v1
v2
v3
v4
v5 (latest)
Automated versus do-it-yourself methods for causal inference: Lessons learned from a data analysis competition
9 July 2017
Vincent Dorie
J. Hill
Uri Shalit
M. Scott
D. Cervone
CML
Re-assign community
ArXiv (abs)
PDF
HTML
Papers citing
"Automated versus do-it-yourself methods for causal inference: Lessons learned from a data analysis competition"
50 / 123 papers shown
Orthogonal Representation Learning for Estimating Causal Quantities
Valentyn Melnychuk
Dennis Frauen
Jonas Schweisthal
Stefan Feuerriegel
CML
OOD
587
6
0
10 Apr 2026
Learning Subgroups with Maximum Treatment Effects without Causal Heuristics
Lincen Yang
Zhong Li
M. Leeuwen
Saber Salehkaleybar
CML
187
0
0
25 Nov 2025
Beyond Multiple Choice: Verifiable OpenQA for Robust Vision-Language RFT
Y. Liu
Hao Li
Haiyu Xu
Baoqi Pei
Jiahao Wang
...
Zheqi He
JG Yao
Bowen Qin
Xi Yang
J. Zhang
OffRL
429
0
0
21 Nov 2025
Improving the Generation and Evaluation of Synthetic Data for Downstream Medical Causal Inference
Harry Amad
Zhaozhi Qian
Dennis Frauen
Julianna Piskorz
Stefan Feuerriegel
Mihaela van der Schaar
CML
276
3
0
21 Oct 2025
Overlap-Adaptive Regularization for Conditional Average Treatment Effect Estimation
Valentyn Melnychuk
Dennis Frauen
Jonas Schweisthal
Stefan Feuerriegel
CML
227
1
0
29 Sep 2025
GDR-learners: Orthogonal Learning of Generative Models for Potential Outcomes
Valentyn Melnychuk
Stefan Feuerriegel
126
0
0
26 Sep 2025
CausalKANs: interpretable treatment effect estimation with Kolmogorov-Arnold networks
Alejandro Almodóvar
Patricia A. Apellániz
Santiago Zazo
J. Parras
CML
357
1
0
26 Sep 2025
Improving Generative Methods for Causal Evaluation via Simulation-Based Inference
Pracheta Amaranath
Vinitra Muralikrishnan
Amit Sharma
David D. Jensen
CML
ELM
149
0
0
02 Sep 2025
Position: Causal Machine Learning Requires Rigorous Synthetic Experiments for Broader Adoption
Audrey Poinsot
Panayiotis Panayiotou
Alessandro Leite
Nicolas Chesneau
Özgür Şimşek
Marc Schoenauer
CML
ELM
162
1
0
12 Aug 2025
Horseshoe Forests for High-Dimensional Causal Survival Analysis
Tijn Jacobs
Wessel N. van Wieringen
Stéphanie L. van der Pas
CML
278
0
0
29 Jul 2025
Honesty in Causal Forests: When It Helps and When It Hurts
Yanfang Hou
Carlos Fernández-Loría
178
0
0
16 Jun 2025
Hybrid Meta-learners for Estimating Heterogeneous Treatment Effects
Zhongyuan Liang
L. Laan
Ahmed Alaa
270
0
0
16 Jun 2025
CausalPFN: Amortized Causal Effect Estimation via In-Context Learning
Vahid Balazadeh
Hamidreza Kamkari
Valentin Thomas
Benson Li
Junwei Ma
Jesse C. Cresswell
Rahul G. Krishnan
CML
265
19
0
09 Jun 2025
TabPFN: One Model to Rule Them All?
Qiong Zhang
Yan Shuo Tan
Qinglong Tian
Pengfei Li
441
12
0
26 May 2025
ReLU integral probability metric and its applications
Yuha Park
Kunwoong Kim
Insung Kong
Yongdai Kim
352
0
0
26 Apr 2025
CausalRivers -- Scaling up benchmarking of causal discovery for real-world time-series
International Conference on Learning Representations (ICLR), 2025
Gideon Stein
M. Shadaydeh
Jan Blunk
Niklas Penzel
Joachim Denzler
AI4TS
393
11
0
21 Mar 2025
KANITE: Kolmogorov-Arnold Networks for ITE estimation
Eshan Mehendale
Abhinav Thorat
Ravi Kolla
N. Pedanekar
CML
397
3
0
18 Mar 2025
CausalMan: A physics-based simulator for large-scale causality
Nicholas Tagliapietra
J. Luettin
Lavdim Halilaj
Moritz Willig
Tim Pychynski
Kristian Kersting
CML
457
0
0
18 Feb 2025
Conformal Inference of Individual Treatment Effects Using Conditional Density Estimates
AAAI Conference on Artificial Intelligence (AAAI), 2025
Baozhen Wang
Xingye Qiao
492
4
0
28 Jan 2025
Oblique Bayesian additive regression trees
Paul-Hieu V. Nguyen
Ryan Yee
Sameer K. Deshpande
186
0
0
13 Nov 2024
Very fast Bayesian Additive Regression Trees on GPU
Giacomo Petrillo
281
1
0
30 Oct 2024
DAG-aware Transformer for Causal Effect Estimation
Manqing Liu
David R. Bellamy
Andrew L. Beam
CML
307
5
0
13 Oct 2024
Towards Representation Learning for Weighting Problems in Design-Based Causal Inference
Conference on Uncertainty in Artificial Intelligence (UAI), 2024
Oscar Clivio
Avi Feller
Chris Holmes
CML
OOD
404
6
0
24 Sep 2024
Generalized Encouragement-Based Instrumental Variables for Counterfactual Regression
Anpeng Wu
Kun Kuang
Ruoxuan Xiong
Xiangwei Chen
Zexu Sun
Fei Wu
Kun Zhang
CML
214
0
0
10 Aug 2024
Distilling interpretable causal trees from causal forests
Patrick Rehill
CML
255
1
0
02 Aug 2024
Robust CATE Estimation Using Novel Ensemble Methods
Oshri Machluf
Tzviel Frostig
Gal Shoham
T. Milo
Elad Berkman
Raviv Pryluk
CML
371
0
0
04 Jul 2024
Improve ROI with Causal Learning and Conformal Prediction
Meng Ai
Zhuo Chen
Jibin Wang
Jing Shang
Tao Tao
Zhen Li
320
3
0
01 Jul 2024
IncomeSCM: From tabular data set to time-series simulator and causal estimation benchmark
Fredrik D. Johansson
CML
332
0
0
25 May 2024
Revisiting Counterfactual Regression through the Lens of Gromov-Wasserstein Information Bottleneck
Hao Yang
Zexu Sun
Hongteng Xu
Xu Chen
371
6
0
24 May 2024
Generalization Bounds for Causal Regression: Insights, Guarantees and Sensitivity Analysis
International Conference on Machine Learning (ICML), 2024
Daniel Csillag
C. Struchiner
G. Goedert
OOD
CML
290
4
0
15 May 2024
Neyman Meets Causal Machine Learning: Experimental Evaluation of Individualized Treatment Rules
Michael Lingzhi Li
Kosuke Imai
CML
276
1
0
25 Apr 2024
Unveiling the Potential of Robustness in Evaluating Causal Inference Models
Yiyan Huang
Cheuk Hang Leung
Siyi Wang
Yijun Li
Qi Wu
OOD
CML
231
1
0
28 Feb 2024
Federated Learning for Estimating Heterogeneous Treatment Effects
Disha Makhija
Joydeep Ghosh
Yejin Kim
CML
FedML
400
3
0
27 Feb 2024
The CATT SATT on the MATT: semiparametric inference for sample treatment effects on the treated
Andrew Yiu
CML
606
0
0
08 Feb 2024
Conformal Convolution and Monte Carlo Meta-learners for Predictive Inference of Individual Treatment Effects
Jef Jonkers
Jarne Verhaeghe
Glenn Van Wallendael
Luc Duchateau
Sofie Van Hoecke
803
6
0
07 Feb 2024
The Essential Role of Causality in Foundation World Models for Embodied AI
Tarun Gupta
Wenbo Gong
Chao Ma
Nick Pawlowski
Agrin Hilmkil
...
Jianfeng Gao
Stefan Bauer
Danica Kragic
Bernhard Schölkopf
Cheng Zhang
327
28
0
06 Feb 2024
A flexible Bayesian g-formula for causal survival analyses with time-dependent confounding
Xinyuan Chen
Liangyuan Hu
Fan Li
CML
356
2
0
04 Feb 2024
Hierarchical Bias-Driven Stratification for Interpretable Causal Effect Estimation
Lucile Ter-Minassian
Liran Szlak
Ehud Karavani
Chris Holmes
Y. Shimoni
215
2
0
31 Jan 2024
Proximal Causal Inference With Text Data
Neural Information Processing Systems (NeurIPS), 2024
Jacob M. Chen
Rohit Bhattacharya
Katherine A. Keith
364
6
0
12 Jan 2024
Deep Copula-Based Survival Analysis for Dependent Censoring with Identifiability Guarantees
Weijia Zhang
Chun Kai Ling
Xuanhui Zhang
CML
OOD
539
12
0
24 Dec 2023
Uncertainty Quantification in Heterogeneous Treatment Effect Estimation with Gaussian-Process-Based Partially Linear Model
AAAI Conference on Artificial Intelligence (AAAI), 2023
Shunsuke Horii
Yoichi Chikahara
226
8
0
16 Dec 2023
SpaCE: The Spatial Confounding Environment
International Conference on Learning Representations (ICLR), 2023
Mauricio Tec
A. Trisovic
Michelle Audirac
Sophie Woodward
Jie Kate Hu
N. Khoshnevis
Francesca Dominici
CML
427
6
0
01 Dec 2023
Adversarial Distribution Balancing for Counterfactual Reasoning
Stefan Schrod
Fabian H. Sinz
Michael Altenbuchinger
OOD
CML
283
1
0
28 Nov 2023
Causal Q-Aggregation for CATE Model Selection
International Conference on Artificial Intelligence and Statistics (AISTATS), 2023
Hui Lan
Vasilis Syrgkanis
CML
473
5
0
25 Oct 2023
Transparency challenges in policy evaluation with causal machine learning -- improving usability and accountability
Patrick Rehill
Nicholas Biddle
CML
ELM
299
10
0
20 Oct 2023
Causal Dynamic Variational Autoencoder for Counterfactual Regression in Longitudinal Data
Mouad El Bouchattaoui
Myriam Tami
Benoit Lepetit
P. Cournède
CML
OOD
538
2
0
16 Oct 2023
Statistical Performance Guarantee for Subgroup Identification with Generic Machine Learning
Michael Lingzhi Li
Kosuke Imai
CML
382
2
0
12 Oct 2023
Conformal Meta-learners for Predictive Inference of Individual Treatment Effects
Neural Information Processing Systems (NeurIPS), 2023
Ahmed Alaa
Zaid Ahmad
Mark van der Laan
CML
377
23
0
28 Aug 2023
RCT Rejection Sampling for Causal Estimation Evaluation
Katherine A. Keith
Sergey Feldman
David Jurgens
Jonathan Bragg
Rohit Bhattacharya
CML
445
10
0
27 Jul 2023
Semiparametric posterior corrections
Andrew Yiu
Edwin Fong
Chris Holmes
Judith Rousseau
466
10
0
09 Jun 2023
1
2
3
Next
Page 1 of 3
