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Causal machine learning for predicting treatment outcomes

Causal machine learning for predicting treatment outcomes

11 October 2024
Stefan Feuerriegel
Dennis Frauen
Valentyn Melnychuk
J. Schweisthal
Konstantin Hess
Alicia Curth
Stefan Bauer
Niki Kilbertus
Isaac S. Kohane
Mihaela van der Schaar
    CML
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Papers citing "Causal machine learning for predicting treatment outcomes"

12 / 12 papers shown
Title
AI-Driven Automation Can Become the Foundation of Next-Era Science of Science Research
AI-Driven Automation Can Become the Foundation of Next-Era Science of Science Research
Renqi Chen
Haoyang Su
Shixiang Tang
Zhenfei Yin
Qi Wu
Hui Li
Ye Sun
Nanqing Dong
Wanli Ouyang
Philip Torr
AI4CE
7
0
0
17 May 2025
Integrating Probabilistic Trees and Causal Networks for Clinical and Epidemiological Data
Sheresh Zahoor
Pietro Liò
G. Dias
Mohammed Hasanuzzaman
46
0
0
28 Jan 2025
Quantifying Aleatoric Uncertainty of the Treatment Effect: A Novel Orthogonal Learner
Quantifying Aleatoric Uncertainty of the Treatment Effect: A Novel Orthogonal Learner
Valentyn Melnychuk
Stefan Feuerriegel
M. Schaar
CML
56
2
0
05 Nov 2024
Learning Representations of Instruments for Partial Identification of
  Treatment Effects
Learning Representations of Instruments for Partial Identification of Treatment Effects
J. Schweisthal
Dennis Frauen
Maresa Schröder
Konstantin Hess
Niki Kilbertus
Stefan Feuerriegel
CML
34
1
0
11 Oct 2024
Stabilized Neural Prediction of Potential Outcomes in Continuous Time
Stabilized Neural Prediction of Potential Outcomes in Continuous Time
Konstantin Hess
Stefan Feuerriegel
53
0
0
04 Oct 2024
Model-agnostic meta-learners for estimating heterogeneous treatment effects over time
Model-agnostic meta-learners for estimating heterogeneous treatment effects over time
Dennis Frauen
Konstantin Hess
Stefan Feuerriegel
37
5
0
07 Jul 2024
Deriving Causal Order from Single-Variable Interventions: Guarantees & Algorithm
Deriving Causal Order from Single-Variable Interventions: Guarantees & Algorithm
Mathieu Chevalley
Patrick Schwab
Arash Mehrjou
46
1
0
28 May 2024
Smoke and Mirrors in Causal Downstream Tasks
Smoke and Mirrors in Causal Downstream Tasks
Riccardo Cadei
Lukas Lindorfer
Sylvia Cremer
Cordelia Schmid
Francesco Locatello
CML
38
3
0
27 May 2024
Conformal Convolution and Monte Carlo Meta-learners for Predictive Inference of Individual Treatment Effects
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
28
2
0
07 Feb 2024
Causal Machine Learning for Cost-Effective Allocation of Development Aid
Causal Machine Learning for Cost-Effective Allocation of Development Aid
Milan Kuzmanovic
Dennis Frauen
Tobias Hatt
Stefan Feuerriegel
32
7
0
30 Jan 2024
A Neural Framework for Generalized Causal Sensitivity Analysis
A Neural Framework for Generalized Causal Sensitivity Analysis
Dennis Frauen
F. Imrie
Alicia Curth
Valentyn Melnychuk
Stefan Feuerriegel
M. Schaar
CML
31
10
0
27 Nov 2023
Bounds on Representation-Induced Confounding Bias for Treatment Effect
  Estimation
Bounds on Representation-Induced Confounding Bias for Treatment Effect Estimation
Valentyn Melnychuk
Dennis Frauen
Stefan Feuerriegel
CML
32
9
0
19 Nov 2023
1