ResearchTrend.AI
  • Communities
  • Connect sessions
  • AI calendar
  • Organizations
  • Join Slack
  • Contact Sales
Papers
Communities
Social Events
Terms and Conditions
Pricing
Contact Sales
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2026 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2101.10943
  4. Cited By
Nonparametric Estimation of Heterogeneous Treatment Effects: From Theory
  to Learning Algorithms
v1v2 (latest)

Nonparametric Estimation of Heterogeneous Treatment Effects: From Theory to Learning Algorithms

International Conference on Artificial Intelligence and Statistics (AISTATS), 2021
26 January 2021
Alicia Curth
M. Schaar
    CML
ArXiv (abs)PDFHTML

Papers citing "Nonparametric Estimation of Heterogeneous Treatment Effects: From Theory to Learning Algorithms"

50 / 118 papers shown
Benchmarking for Deep Uplift Modeling in Online Marketing
Benchmarking for Deep Uplift Modeling in Online Marketing
Dugang Liu
Xing Tang
Yang Qiao
Miao Liu
Zexu Sun
Xiuqiang He
Zhong Ming
280
2
0
01 Jun 2024
Conformal Counterfactual Inference under Hidden Confounding
Conformal Counterfactual Inference under Hidden Confounding
Zonghao Chen
Ruocheng Guo
Jean-François Ton
Yang Liu
CMLOffRL
481
6
0
20 May 2024
Generalization Bounds for Causal Regression: Insights, Guarantees and
  Sensitivity Analysis
Generalization Bounds for Causal Regression: Insights, Guarantees and Sensitivity AnalysisInternational Conference on Machine Learning (ICML), 2024
Daniel Csillag
C. Struchiner
G. Goedert
OODCML
235
3
0
15 May 2024
Differentiable Pareto-Smoothed Weighting for High-Dimensional
  Heterogeneous Treatment Effect Estimation
Differentiable Pareto-Smoothed Weighting for High-Dimensional Heterogeneous Treatment Effect Estimation
Yoichi Chikahara
Kansei Ushiyama
428
0
0
26 Apr 2024
Neural Networks with Causal Graph Constraints: A New Approach for
  Treatment Effects Estimation
Neural Networks with Causal Graph Constraints: A New Approach for Treatment Effects Estimation
Roger Pros
Jordi Vitrià
CML
257
0
0
18 Apr 2024
KG-TREAT: Pre-training for Treatment Effect Estimation by Synergizing
  Patient Data with Knowledge Graphs
KG-TREAT: Pre-training for Treatment Effect Estimation by Synergizing Patient Data with Knowledge Graphs
Ruoqi Liu
Lingfei Wu
Ping Zhang
165
3
0
06 Mar 2024
Triple/Debiased Lasso for Statistical Inference of Conditional Average
  Treatment Effects
Triple/Debiased Lasso for Statistical Inference of Conditional Average Treatment Effects
Masahiro Kato
CML
293
1
0
05 Mar 2024
Defining Expertise: Applications to Treatment Effect Estimation
Defining Expertise: Applications to Treatment Effect Estimation
Alihan Huyuk
Qiyao Wei
Alicia Curth
M. Schaar
CML
231
3
0
01 Mar 2024
Unveiling the Potential of Robustness in Evaluating Causal Inference
  Models
Unveiling the Potential of Robustness in Evaluating Causal Inference Models
Yiyan Huang
Cheuk Hang Leung
Siyi Wang
Yijun Li
Qi Wu
OODCML
201
1
0
28 Feb 2024
Federated Learning for Estimating Heterogeneous Treatment Effects
Federated Learning for Estimating Heterogeneous Treatment Effects
Disha Makhija
Joydeep Ghosh
Yejin Kim
CMLFedML
376
3
0
27 Feb 2024
Towards AI-Based Precision Oncology: A Machine Learning Framework for Personalized Counterfactual Treatment Suggestions based on Multi-Omics Data
Manuel Schürch
Laura Boos
V. Heinzelmann-Schwarz
Gabriele Gut
Michael Krauthammer
Andreas Wicki
Tumor Profiler Consortium
213
6
0
19 Feb 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
744
5
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
348
13
0
30 Jan 2024
Adversarial Distribution Balancing for Counterfactual Reasoning
Adversarial Distribution Balancing for Counterfactual Reasoning
Stefan Schrod
Fabian H. Sinz
Michael Altenbuchinger
OODCML
236
1
0
28 Nov 2023
A Neural Framework for Generalized Causal Sensitivity Analysis
A Neural Framework for Generalized Causal Sensitivity AnalysisInternational Conference on Learning Representations (ICLR), 2023
Dennis Frauen
F. Imrie
Alicia Curth
Valentyn Melnychuk
Stefan Feuerriegel
M. Schaar
CML
304
11
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
327
19
0
19 Nov 2023
Estimating treatment effects from single-arm trials via latent-variable
  modeling
Estimating treatment effects from single-arm trials via latent-variable modelingInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2023
Manuel Haussmann
Tran Minh Son Le
Viivi Halla-aho
Samu Kurki
Jussi Leinonen
Miika Koskinen
Samuel Kaski
Harri Lähdesmäki
CML
364
0
0
06 Nov 2023
Bayesian Neural Controlled Differential Equations for Treatment Effect
  Estimation
Bayesian Neural Controlled Differential Equations for Treatment Effect EstimationInternational Conference on Learning Representations (ICLR), 2023
Konstantin Hess
Valentyn Melnychuk
Dennis Frauen
Stefan Feuerriegel
241
22
0
26 Oct 2023
CATE Lasso: Conditional Average Treatment Effect Estimation with
  High-Dimensional Linear Regression
CATE Lasso: Conditional Average Treatment Effect Estimation with High-Dimensional Linear Regression
Masahiro Kato
Masaaki Imaizumi
CML
302
2
0
25 Oct 2023
Assessing Electricity Service Unfairness with Transfer Counterfactual
  Learning
Assessing Electricity Service Unfairness with Transfer Counterfactual Learning
S. Wei
Xiangrui Kong
Á. Xavier
Shixiang Zhu
Yao Xie
Feng Qiu
248
2
0
05 Oct 2023
Uplift vs. predictive modeling: a theoretical analysis
Uplift vs. predictive modeling: a theoretical analysis
Théo Verhelst
Robin Petit
Wouter Verbeke
Gianluca Bontempi
150
2
0
21 Sep 2023
The Connection Between R-Learning and Inverse-Variance Weighting for
  Estimation of Heterogeneous Treatment Effects
The Connection Between R-Learning and Inverse-Variance Weighting for Estimation of Heterogeneous Treatment Effects
Aaron Fisher
CML
309
2
0
19 Jul 2023
Assisting Clinical Decisions for Scarcely Available Treatment via
  Disentangled Latent Representation
Assisting Clinical Decisions for Scarcely Available Treatment via Disentangled Latent RepresentationKnowledge Discovery and Data Mining (KDD), 2023
Bing Xue
A. Said
Ziqi Xu
Hanyang Liu
N. Shah
Hanqing Yang
Philip R. O. Payne
Chenyang Lu
217
6
0
06 Jul 2023
Accounting For Informative Sampling When Learning to Forecast Treatment
  Outcomes Over Time
Accounting For Informative Sampling When Learning to Forecast Treatment Outcomes Over TimeInternational Conference on Machine Learning (ICML), 2023
Toon Vanderschueren
Alicia Curth
Wouter Verbeke
M. Schaar
291
16
0
07 Jun 2023
Partial Counterfactual Identification of Continuous Outcomes with a
  Curvature Sensitivity Model
Partial Counterfactual Identification of Continuous Outcomes with a Curvature Sensitivity ModelNeural Information Processing Systems (NeurIPS), 2023
Valentyn Melnychuk
Dennis Frauen
Stefan Feuerriegel
529
13
0
02 Jun 2023
Explicit Feature Interaction-aware Uplift Network for Online Marketing
Explicit Feature Interaction-aware Uplift Network for Online MarketingKnowledge Discovery and Data Mining (KDD), 2023
Dugang Liu
Xing Tang
Han Gao
Fuyuan Lyu
Xiuqiang He
165
28
0
01 Jun 2023
Sharp Bounds for Generalized Causal Sensitivity Analysis
Sharp Bounds for Generalized Causal Sensitivity AnalysisNeural Information Processing Systems (NeurIPS), 2023
Dennis Frauen
Valentyn Melnychuk
Stefan Feuerriegel
CML
374
25
0
26 May 2023
Dynamic Inter-treatment Information Sharing for Individualized Treatment
  Effects Estimation
Dynamic Inter-treatment Information Sharing for Individualized Treatment Effects EstimationInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2023
V. Chauhan
Jiandong Zhou
Ghadeer O. Ghosheh
Soheila Molaei
David Clifton
349
13
0
25 May 2023
Meta-learning for heterogeneous treatment effect estimation with
  closed-form solvers
Meta-learning for heterogeneous treatment effect estimation with closed-form solversMachine-mediated learning (ML), 2023
Tomoharu Iwata
Yoichi Chikahara
CMLFedML
209
2
0
19 May 2023
Fair Off-Policy Learning from Observational Data
Fair Off-Policy Learning from Observational DataInternational Conference on Machine Learning (ICML), 2023
Dennis Frauen
Valentyn Melnychuk
Stefan Feuerriegel
FaMLOffRL
333
8
0
15 Mar 2023
Understanding the Impact of Competing Events on Heterogeneous Treatment
  Effect Estimation from Time-to-Event Data
Understanding the Impact of Competing Events on Heterogeneous Treatment Effect Estimation from Time-to-Event DataInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2023
Alicia Curth
M. Schaar
CML
175
5
0
23 Feb 2023
In Search of Insights, Not Magic Bullets: Towards Demystification of the
  Model Selection Dilemma in Heterogeneous Treatment Effect Estimation
In Search of Insights, Not Magic Bullets: Towards Demystification of the Model Selection Dilemma in Heterogeneous Treatment Effect EstimationInternational Conference on Machine Learning (ICML), 2023
Alicia Curth
M. Schaar
CML
281
34
0
06 Feb 2023
Zero-shot causal learning
Zero-shot causal learningNeural Information Processing Systems (NeurIPS), 2023
H. Nilforoshan
Michael Moor
Yusuf Roohani
Yining Chen
Anja vSurina
Michihiro Yasunaga
Sara Oblak
J. Leskovec
CMLBDLOffRL
316
18
0
28 Jan 2023
Meta-analysis of individualized treatment rules via sign-coherency
Meta-analysis of individualized treatment rules via sign-coherency
Jay Jojo Cheng
J. Huling
Guanhua Chen
160
1
0
28 Nov 2022
BENK: The Beran Estimator with Neural Kernels for Estimating the
  Heterogeneous Treatment Effect
BENK: The Beran Estimator with Neural Kernels for Estimating the Heterogeneous Treatment Effect
Stanislav R. Kirpichenko
Lev V. Utkin
A. Konstantinov
CML
279
0
0
19 Nov 2022
Partial counterfactual identification and uplift modeling: theoretical
  results and real-world assessment
Partial counterfactual identification and uplift modeling: theoretical results and real-world assessmentMachine-mediated learning (ML), 2022
Théo Verhelst
Denis Mercier
Jeevan Shrestha
Gianluca Bontempi
CML
156
3
0
14 Nov 2022
NESTER: An Adaptive Neurosymbolic Method for Causal Effect Estimation
NESTER: An Adaptive Neurosymbolic Method for Causal Effect EstimationAAAI Conference on Artificial Intelligence (AAAI), 2022
Abbavaram Gowtham Reddy
V. Balasubramanian
CML
376
1
0
08 Nov 2022
Flexible machine learning estimation of conditional average treatment
  effects: a blessing and a curse
Flexible machine learning estimation of conditional average treatment effects: a blessing and a curse
Richard Post
Isabel L. van den Heuvel
M. Petković
Edwin R. van den Heuvel
CML
102
3
0
29 Oct 2022
Adversarial De-confounding in Individualised Treatment Effects
  Estimation
Adversarial De-confounding in Individualised Treatment Effects EstimationInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2022
Vinod Kumar Chauhan
Soheila Molaei
Marzia Hoque Tania
Anshul Thakur
T. Zhu
David Clifton
CML
269
17
0
19 Oct 2022
Transfer Learning on Heterogeneous Feature Spaces for Treatment Effects
  Estimation
Transfer Learning on Heterogeneous Feature Spaces for Treatment Effects EstimationNeural Information Processing Systems (NeurIPS), 2022
Ioana Bica
M. Schaar
OODCML
190
26
0
08 Oct 2022
A Survey of Deep Causal Models and Their Industrial Applications
A Survey of Deep Causal Models and Their Industrial ApplicationsArtificial Intelligence Review (Artif Intell Rev), 2022
Zongyu Li
Xiaoning Guo
Siwei Qiang
CMLAI4CE
586
16
0
19 Sep 2022
Normalizing Flows for Interventional Density Estimation
Normalizing Flows for Interventional Density EstimationInternational Conference on Machine Learning (ICML), 2022
Valentyn Melnychuk
Dennis Frauen
Stefan Feuerriegel
434
23
0
13 Sep 2022
Estimating individual treatment effects under unobserved confounding
  using binary instruments
Estimating individual treatment effects under unobserved confounding using binary instrumentsInternational Conference on Learning Representations (ICLR), 2022
Dennis Frauen
Stefan Feuerriegel
CML
342
24
0
17 Aug 2022
Heterogeneous Treatment Effect with Trained Kernels of the
  Nadaraya-Watson Regression
Heterogeneous Treatment Effect with Trained Kernels of the Nadaraya-Watson Regression
A. Konstantinov
Stanislav R. Kirpichenko
Lev V. Utkin
CML
199
5
0
19 Jul 2022
Benchmarking Heterogeneous Treatment Effect Models through the Lens of
  Interpretability
Benchmarking Heterogeneous Treatment Effect Models through the Lens of InterpretabilityNeural Information Processing Systems (NeurIPS), 2022
Jonathan Crabbé
Alicia Curth
Ioana Bica
M. Schaar
CML
281
22
0
16 Jun 2022
Comparison of meta-learners for estimating multi-valued treatment
  heterogeneous effects
Comparison of meta-learners for estimating multi-valued treatment heterogeneous effectsInternational Conference on Machine Learning (ICML), 2022
Naoufal Acharki
Ramiro Lugo
A. Bertoncello
Josselin Garnier
CML
255
16
0
29 May 2022
Generalization bounds and algorithms for estimating conditional average
  treatment effect of dosage
Generalization bounds and algorithms for estimating conditional average treatment effect of dosage
Alexis Bellot
Anish Dhir
G. Prando
CML
194
12
0
29 May 2022
Causal Machine Learning for Healthcare and Precision Medicine
Causal Machine Learning for Healthcare and Precision MedicineRoyal Society Open Science (RSOS), 2022
Pedro Sanchez
J. Voisey
Tian Xia
Hannah I. Watson
Alison Q. OÑeil
Sotirios A. Tsaftaris
OODCML
311
181
0
23 May 2022
Causal Transformer for Estimating Counterfactual Outcomes
Causal Transformer for Estimating Counterfactual OutcomesInternational Conference on Machine Learning (ICML), 2022
Valentyn Melnychuk
Dennis Frauen
Stefan Feuerriegel
CML
275
131
0
14 Apr 2022
Experimental Standards for Deep Learning in Natural Language Processing
  Research
Experimental Standards for Deep Learning in Natural Language Processing ResearchConference on Empirical Methods in Natural Language Processing (EMNLP), 2022
Dennis Ulmer
Elisa Bassignana
Max Müller-Eberstein
Daniel Varab
Mike Zhang
Rob van der Goot
Christian Hardmeier
Barbara Plank
270
12
0
13 Apr 2022
Previous
123
Next
Page 2 of 3