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Generalized Optimal Matching Methods for Causal Inference
v1v2v3 (latest)

Generalized Optimal Matching Methods for Causal Inference

Journal of machine learning research (JMLR), 2016
26 December 2016
Nathan Kallus
ArXiv (abs)PDFHTML

Papers citing "Generalized Optimal Matching Methods for Causal Inference"

50 / 59 papers shown
A Sensitivity Approach to Causal Inference Under Limited Overlap
A Sensitivity Approach to Causal Inference Under Limited Overlap
Yuanzhe Ma
Hongseok Namkoong
CML
439
0
0
27 Nov 2025
Structure Maintained Representation Learning Neural Network for Causal Inference
Structure Maintained Representation Learning Neural Network for Causal Inference
Yang Sun
Wenbin Lu
Yi-Hui Zhou
OODCML
159
0
0
03 Aug 2025
Federated Instrumental Variable Analysis via Federated Generalized Method of Moments
Federated Instrumental Variable Analysis via Federated Generalized Method of Moments
Geetika
Somya Tyagi
Bapi Chatterjee
FedML
250
0
0
27 May 2025
Forests for Differences: Robust Causal Inference Beyond Parametric DiD
Forests for Differences: Robust Causal Inference Beyond Parametric DiD
Hugo Gobato Souto
Francisco Louzada Neto
230
0
0
14 May 2025
A primer on optimal transport for causal inference with observational data
A primer on optimal transport for causal inference with observational data
Florian F Gunsilius
OTCML
349
4
0
10 Mar 2025
Multivariate root-n-consistent smoothing parameter free matching estimators and estimators of inverse density weighted expectations
Multivariate root-n-consistent smoothing parameter free matching estimators and estimators of inverse density weighted expectations
H. Holzmann
A. Meister
324
1
0
17 Feb 2025
Towards Representation Learning for Weighting Problems in Design-Based Causal Inference
Towards Representation Learning for Weighting Problems in Design-Based Causal InferenceConference on Uncertainty in Artificial Intelligence (UAI), 2024
Oscar Clivio
Avi Feller
Chris Holmes
CMLOOD
404
6
0
24 Sep 2024
Scalable kernel balancing weights in a nationwide observational study of
  hospital profit status and heart attack outcomes
Scalable kernel balancing weights in a nationwide observational study of hospital profit status and heart attack outcomes
Kwangho Kim
B. Niknam
J. Zubizarreta
241
4
0
01 Nov 2023
A Stable and Efficient Covariate-Balancing Estimator for Causal Survival
  Effects
A Stable and Efficient Covariate-Balancing Estimator for Causal Survival Effects
Khiem Pham
David A. Hirshberg
Phuong-Mai Huynh-Pham
Michele Santacatterina
Ser-Nam Lim
Ramin Zabih
370
1
0
01 Oct 2023
De-confounding Representation Learning for Counterfactual Inference on
  Continuous Treatment via Generative Adversarial Network
De-confounding Representation Learning for Counterfactual Inference on Continuous Treatment via Generative Adversarial NetworkData mining and knowledge discovery (DMKD), 2023
Yonghe Zhao
Q. Huang
Haolong Zeng
Yun-Wen Pen
Huashan Sun
CMLOODBDL
119
3
0
24 Jul 2023
Reliable Off-Policy Learning for Dosage Combinations
Reliable Off-Policy Learning for Dosage CombinationsNeural Information Processing Systems (NeurIPS), 2023
Jonas Schweisthal
Dennis Frauen
Valentyn Melnychuk
Stefan Feuerriegel
OffRL
333
15
0
31 May 2023
Matched Machine Learning: A Generalized Framework for Treatment Effect
  Inference With Learned Metrics
Matched Machine Learning: A Generalized Framework for Treatment Effect Inference With Learned Metrics
Marco Morucci
Cynthia Rudin
A. Volfovsky
CMLFedML
186
1
0
03 Apr 2023
Pseudo-Labeling for Kernel Ridge Regression under Covariate Shift
Pseudo-Labeling for Kernel Ridge Regression under Covariate Shift
Kaizheng Wang
351
17
0
20 Feb 2023
Kernel-based off-policy estimation without overlap: Instance optimality
  beyond semiparametric efficiency
Kernel-based off-policy estimation without overlap: Instance optimality beyond semiparametric efficiency
Wenlong Mou
Peng Ding
Martin J. Wainwright
Peter L. Bartlett
OffRL
286
12
0
16 Jan 2023
An empirical process framework for covariate balance in causal inference
An empirical process framework for covariate balance in causal inference
Efrén Cruz-Cortés
K. Josey
Fan Yang
Debashis Ghosh
146
0
0
02 Jan 2023
Inference on Strongly Identified Functionals of Weakly Identified
  Functions
Inference on Strongly Identified Functionals of Weakly Identified FunctionsAnnual Conference Computational Learning Theory (COLT), 2022
Andrew Bennett
Nathan Kallus
Xiaojie Mao
Whitney Newey
Vasilis Syrgkanis
Masatoshi Uehara
434
23
0
17 Aug 2022
Outcome Assumptions and Duality Theory for Balancing Weights
Outcome Assumptions and Duality Theory for Balancing WeightsInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2022
David Bruns-Smith
Avi Feller
346
6
0
17 Mar 2022
Neural Score Matching for High-Dimensional Causal Inference
Neural Score Matching for High-Dimensional Causal InferenceInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2022
Oscar Clivio
Fabian Falck
B. Lehmann
George Deligiannidis
Chris Holmes
CML
305
10
0
01 Mar 2022
Estimating causal effects with optimization-based methods: A review and
  empirical comparison
Estimating causal effects with optimization-based methods: A review and empirical comparisonEuropean Journal of Operational Research (EJOR), 2022
Martin Cousineau
V. Verter
Susan Murphy
J. Pineau
CML
198
13
0
28 Feb 2022
Case-based off-policy policy evaluation using prototype learning
Case-based off-policy policy evaluation using prototype learning
Anton Matsson
Fredrik D. Johansson
OffRL
191
1
0
22 Nov 2021
Generalized Kernel Ridge Regression for Causal Inference with
  Missing-at-Random Sample Selection
Generalized Kernel Ridge Regression for Causal Inference with Missing-at-Random Sample Selection
Rahul Singh
281
1
0
09 Nov 2021
Sequential Kernel Embedding for Mediated and Time-Varying Dose Response Curves
Sequential Kernel Embedding for Mediated and Time-Varying Dose Response Curves
Rahul Singh
Liyuan Xu
Arthur Gretton
514
5
0
06 Nov 2021
Projected State-action Balancing Weights for Offline Reinforcement
  Learning
Projected State-action Balancing Weights for Offline Reinforcement LearningAnnals of Statistics (Ann. Stat.), 2021
Jiayi Wang
Zhengling Qi
Raymond K. W. Wong
OffRL
265
24
0
10 Sep 2021
Optimal transport weights for causal inference
Optimal transport weights for causal inference
Eric A. Dunipace
CMLOT
356
12
0
05 Sep 2021
Instrument Space Selection for Kernel Maximum Moment Restriction
Instrument Space Selection for Kernel Maximum Moment Restriction
Rui Zhang
Krikamol Muandet
Bernhard Schölkopf
Masaaki Imaizumi
181
3
0
07 Jun 2021
Robust Sample Weighting to Facilitate Individualized Treatment Rule
  Learning for a Target Population
Robust Sample Weighting to Facilitate Individualized Treatment Rule Learning for a Target PopulationBiometrika (Biometrika), 2021
Rui Chen
J. Huling
Guanhua Chen
Menggang Yu
CML
291
12
0
03 May 2021
NCoRE: Neural Counterfactual Representation Learning for Combinations of
  Treatments
NCoRE: Neural Counterfactual Representation Learning for Combinations of Treatments
S. Parbhoo
Stefan Bauer
Patrick Schwab
CMLBDL
203
21
0
20 Mar 2021
Estimating Average Treatment Effects with Support Vector Machines
Estimating Average Treatment Effects with Support Vector MachinesStatistics in Medicine (Stat. Med.), 2021
Alexander Tarr
Kosuke Imai
210
13
0
23 Feb 2021
Kernel Ridge Riesz Representers: Generalization, Mis-specification, and
  the Counterfactual Effective Dimension
Kernel Ridge Riesz Representers: Generalization, Mis-specification, and the Counterfactual Effective Dimension
Rahul Singh
CML
392
10
0
22 Feb 2021
Double Robust Representation Learning for Counterfactual Prediction
Double Robust Representation Learning for Counterfactual Prediction
Shuxi Zeng
Serge Assaad
Chenyang Tao
Shounak Datta
Lawrence Carin
Fan Li
OODCML
254
6
0
15 Oct 2020
Kernel Methods for Causal Functions: Dose, Heterogeneous, and
  Incremental Response Curves
Kernel Methods for Causal Functions: Dose, Heterogeneous, and Incremental Response Curves
Rahul Singh
Liyuan Xu
Arthur Gretton
OffRL
573
44
0
10 Oct 2020
Off-policy Evaluation in Infinite-Horizon Reinforcement Learning with
  Latent Confounders
Off-policy Evaluation in Infinite-Horizon Reinforcement Learning with Latent ConfoundersInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2020
Andrew Bennett
Nathan Kallus
Lihong Li
Ali Mousavi
OffRL
219
48
0
27 Jul 2020
Comment: Entropy Learning for Dynamic Treatment Regimes
Comment: Entropy Learning for Dynamic Treatment RegimesStatistica sinica (SS), 2020
Nathan Kallus
152
4
0
06 Apr 2020
A Balancing Weight Framework for Estimating the Causal Effect of General
  Treatments
A Balancing Weight Framework for Estimating the Causal Effect of General Treatments
Guillaume Martinet
CML
139
3
0
26 Feb 2020
Generalization Bounds and Representation Learning for Estimation of
  Potential Outcomes and Causal Effects
Generalization Bounds and Representation Learning for Estimation of Potential Outcomes and Causal EffectsJournal of machine learning research (JMLR), 2020
Fredrik D. Johansson
Uri Shalit
Nathan Kallus
David Sontag
CMLOOD
542
123
0
21 Jan 2020
Optimal Experimental Design for Staggered Rollouts
Optimal Experimental Design for Staggered RolloutsManagement Sciences (MS), 2019
Ruoxuan Xiong
Susan Athey
Mohsen Bayati
Guido Imbens
486
40
0
09 Nov 2019
Minimax Weight and Q-Function Learning for Off-Policy Evaluation
Minimax Weight and Q-Function Learning for Off-Policy EvaluationInternational Conference on Machine Learning (ICML), 2019
Masatoshi Uehara
Jiawei Huang
Nan Jiang
OffRL
646
199
0
28 Oct 2019
Kernel Optimal Orthogonality Weighting: A Balancing Approach to
  Estimating Effects of Continuous Treatments
Kernel Optimal Orthogonality Weighting: A Balancing Approach to Estimating Effects of Continuous Treatments
Nathan Kallus
Michele Santacatterina
CML
197
21
0
26 Oct 2019
Optimal Estimation of Generalized Average Treatment Effects using Kernel
  Optimal Matching
Optimal Estimation of Generalized Average Treatment Effects using Kernel Optimal Matching
Nathan Kallus
Michele Santacatterina
CML
176
4
0
13 Aug 2019
Policy Evaluation with Latent Confounders via Optimal Balance
Policy Evaluation with Latent Confounders via Optimal BalanceNeural Information Processing Systems (NeurIPS), 2019
Andrew Bennett
Nathan Kallus
CML
192
19
0
06 Aug 2019
Quantifying Error in the Presence of Confounders for Causal Inference
Quantifying Error in the Presence of Confounders for Causal Inference
Rathin Desai
Amit Sharma
CML
85
0
0
10 Jul 2019
Characterization of Overlap in Observational Studies
Characterization of Overlap in Observational StudiesInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2019
Michael Oberst
Fredrik D. Johansson
Dennis L. Wei
Tian Gao
G. Brat
David Sontag
Kush R. Varshney
CML
198
24
0
09 Jul 2019
General Control Functions for Causal Effect Estimation from Instrumental
  Variables
General Control Functions for Causal Effect Estimation from Instrumental Variables
N. Jethani
Rajesh Ranganath
CML
260
4
0
08 Jul 2019
More Efficient Policy Learning via Optimal Retargeting
More Efficient Policy Learning via Optimal RetargetingJournal of the American Statistical Association (JASA), 2019
Nathan Kallus
OffRL
340
44
0
20 Jun 2019
Deep Generalized Method of Moments for Instrumental Variable Analysis
Deep Generalized Method of Moments for Instrumental Variable AnalysisNeural Information Processing Systems (NeurIPS), 2019
Andrew Bennett
Nathan Kallus
Tobias Schnabel
268
139
0
29 May 2019
Large Sample Properties of Matching for Balance
Large Sample Properties of Matching for BalanceStatistica sinica (Stat. Sinica), 2019
Yixin Wang
J. Zubizarreta
268
4
0
26 May 2019
Minimax Linear Estimation of the Retargeted Mean
Minimax Linear Estimation of the Retargeted Mean
David A. Hirshberg
A. Maleki
J. Zubizarreta
CML
404
41
0
11 Jan 2019
Adversarial Balancing for Causal Inference
Adversarial Balancing for Causal Inference
Michal Ozery-Flato
Pierre Thodoroff
Matan Ninio
Michal Rosen-Zvi
T. El-Hay
CMLGAN
276
27
0
17 Oct 2018
Optimal Balancing of Time-Dependent Confounders for Marginal Structural
  Models
Optimal Balancing of Time-Dependent Confounders for Marginal Structural Models
Nathan Kallus
Michele Santacatterina
146
20
0
04 Jun 2018
Learning Weighted Representations for Generalization Across Designs
Learning Weighted Representations for Generalization Across Designs
Fredrik D. Johansson
Nathan Kallus
Uri Shalit
David Sontag
OOD
313
91
0
23 Feb 2018
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