Communities
Connect sessions
AI calendar
Organizations
Join Slack
Contact Sales
Search
Open menu
Home
Papers
1605.03661
Cited By
v1
v2
v3 (latest)
Learning Representations for Counterfactual Inference
12 May 2016
Fredrik D. Johansson
Uri Shalit
David Sontag
CML
OOD
BDL
Re-assign community
ArXiv (abs)
PDF
HTML
Papers citing
"Learning Representations for Counterfactual Inference"
50 / 432 papers shown
A Theoretical Analysis on Independence-driven Importance Weighting for Covariate-shift Generalization
International Conference on Machine Learning (ICML), 2021
Renzhe Xu
Xingxuan Zhang
Zheyan Shen
Tong Zhang
Peng Cui
OOD
367
32
0
03 Nov 2021
Cycle-Balanced Representation Learning For Counterfactual Inference
SDM (SDM), 2021
Guanglin Zhou
Weitong Chen
Xiwei Xu
Chen Wang
Liming Zhu
CML
OOD
94
12
0
29 Oct 2021
Extracting Expert's Goals by What-if Interpretable Modeling
C. Chang
George Adam
Rich Caruana
Anna Goldenberg
OffRL
221
0
0
28 Oct 2021
Heterogeneous Effects of Software Patches in a Multiplayer Online Battle Arena Game
Yuzi He
Christopher Tran
Julie Jiang
Keith Burghardt
Emilio Ferrara
Elena Zheleva
Kristina Lerman
133
10
0
27 Oct 2021
SurvITE: Learning Heterogeneous Treatment Effects from Time-to-Event Data
Alicia Curth
Changhee Lee
M. Schaar
CML
192
33
0
26 Oct 2021
Causal Effect Estimation using Variational Information Bottleneck
Zhenyu Lu
Yurong Cheng
Mingjun Zhong
G. Stoian
Ye Yuan
Guoren Wang
CML
184
4
0
26 Oct 2021
Covariate Balancing Methods for Randomized Controlled Trials Are Not Adversarially Robust
Hossein Babaei
Sina Alemohammad
Richard Baraniuk
313
0
0
25 Oct 2021
β
β
β
-Intact-VAE: Identifying and Estimating Causal Effects under Limited Overlap
Pengzhou (Abel) Wu
Kenji Fukumizu
CML
198
16
0
11 Oct 2021
Estimating Potential Outcome Distributions with Collaborating Causal Networks
Tianhui Zhou
William E Carson IV
David Carlson
CML
342
10
0
04 Oct 2021
Towards Principled Causal Effect Estimation by Deep Identifiable Models
Pengzhou (Abel) Wu
Kenji Fukumizu
BDL
OOD
CML
248
3
0
30 Sep 2021
Heterogeneous Treatment Effect Estimation using machine learning for Healthcare application: tutorial and benchmark
Journal of Biomedical Informatics (JBI), 2021
Yaobin Ling
Pulakesh Upadhyaya
Luyao Chen
Xiaoqian Jiang
Yejin Kim
CML
422
25
0
27 Sep 2021
Estimating Categorical Counterfactuals via Deep Twin Networks
Athanasios Vlontzos
Bernhard Kainz
Ciarán M. Gilligan-Lee
OOD
CML
BDL
504
21
0
04 Sep 2021
E-Commerce Promotions Personalization via Online Multiple-Choice Knapsack with Uplift Modeling
International Conference on Information and Knowledge Management (CIKM), 2021
Javier Albert
Dmitri Goldenberg
205
35
0
11 Aug 2021
The Bias-Variance Tradeoff of Doubly Robust Estimator with Targeted
L
1
L_1
L
1
regularized Neural Networks Predictions
M. Rostami
O. Saarela
M. Escobar
201
1
0
02 Aug 2021
Doing Great at Estimating CATE? On the Neglected Assumptions in Benchmark Comparisons of Treatment Effect Estimators
Alicia Curth
M. Schaar
CML
127
7
0
28 Jul 2021
CETransformer: Casual Effect Estimation via Transformer Based Representation Learning
Chinese Conference on Pattern Recognition and Computer Vision (CPRCV), 2021
Zhenyu Guo
Shuai Zheng
Zhizhe Liu
Kun Yan
Zhenfeng Zhu
CML
121
17
0
19 Jul 2021
Auto IV: Counterfactual Prediction via Automatic Instrumental Variable Decomposition
Junkun Yuan
Anpeng Wu
Kun Kuang
Yangqiu Song
Runze Wu
Leilei Gan
Lanfen Lin
CML
317
44
0
13 Jul 2021
The Causal-Neural Connection: Expressiveness, Learnability, and Inference
K. Xia
Kai-Zhan Lee
Yoshua Bengio
Elias Bareinboim
CML
345
129
0
02 Jul 2021
Finding Valid Adjustments under Non-ignorability with Minimal DAG Knowledge
International Conference on Artificial Intelligence and Statistics (AISTATS), 2021
Abhin Shah
Karthikeyan Shanmugam
Kartik Ahuja
CML
161
13
0
22 Jun 2021
Costs and Benefits of Fair Regression
Han Zhao
FaML
137
10
0
16 Jun 2021
Contrastive Mixture of Posteriors for Counterfactual Inference, Data Integration and Fairness
Adam Foster
Árpi Vezér
C. A. Glastonbury
Páidí Creed
Sam Abujudeh
Aaron Sim
FaML
197
7
0
15 Jun 2021
Deep Proxy Causal Learning and its Application to Confounded Bandit Policy Evaluation
Neural Information Processing Systems (NeurIPS), 2021
Liyuan Xu
Heishiro Kanagawa
Arthur Gretton
CML
308
45
0
07 Jun 2021
Counterfactual Maximum Likelihood Estimation for Training Deep Networks
Neural Information Processing Systems (NeurIPS), 2021
Xinyi Wang
Wenhu Chen
Michael Stephen Saxon
Wenjie Wang
OOD
CML
BDL
284
8
0
07 Jun 2021
On Inductive Biases for Heterogeneous Treatment Effect Estimation
Neural Information Processing Systems (NeurIPS), 2021
Alicia Curth
M. Schaar
CML
353
99
0
07 Jun 2021
Learning from Counterfactual Links for Link Prediction
International Conference on Machine Learning (ICML), 2021
Tong Zhao
Gang Liu
Daheng Wang
Wenhao Yu
Meng Jiang
CML
OOD
288
116
0
03 Jun 2021
Causal Effect Inference for Structured Treatments
Neural Information Processing Systems (NeurIPS), 2021
Jean Kaddour
Yuchen Zhu
Qi Liu
Matt J. Kusner
Ricardo M. A. Silva
CML
488
53
0
03 Jun 2021
Causally motivated Shortcut Removal Using Auxiliary Labels
International Conference on Artificial Intelligence and Statistics (AISTATS), 2021
Maggie Makar
Ben Packer
D. Moldovan
Davis W. Blalock
Yoni Halpern
Alexander DÁmour
OOD
CML
265
82
0
13 May 2021
Neural Networks for Learning Counterfactual G-Invariances from Single Environments
International Conference on Learning Representations (ICLR), 2021
S Chandra Mouli
Bruno Ribeiro
OOD
183
13
0
20 Apr 2021
Sequential Deconfounding for Causal Inference with Unobserved Confounders
CLEaR (CLEaR), 2021
Tobias Hatt
Stefan Feuerriegel
CML
318
30
0
16 Apr 2021
Deconfounding Scores: Feature Representations for Causal Effect Estimation with Weak Overlap
Alexander DÁmour
Alexander M. Franks
CML
145
11
0
12 Apr 2021
Matched sample selection with GANs for mitigating attribute confounding
Chandan Singh
Guha Balakrishnan
Pietro Perona
GAN
159
7
0
24 Mar 2021
NCoRE: Neural Counterfactual Representation Learning for Combinations of Treatments
S. Parbhoo
Stefan Bauer
Patrick Schwab
CML
BDL
150
21
0
20 Mar 2021
VCNet and Functional Targeted Regularization For Learning Causal Effects of Continuous Treatments
International Conference on Learning Representations (ICLR), 2021
Lizhen Nie
Mao Ye
Qiang Liu
D. Nicolae
CML
169
78
0
14 Mar 2021
Treatment Effect Estimation using Invariant Risk Minimization
IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2021
Abhin Shah
Kartik Ahuja
Karthikeyan Shanmugam
Dennis L. Wei
Kush R. Varshney
Amit Dhurandhar
CML
OOD
128
3
0
13 Mar 2021
Limitations of Post-Hoc Feature Alignment for Robustness
Computer Vision and Pattern Recognition (CVPR), 2021
Collin Burns
Jacob Steinhardt
OOD
194
23
0
10 Mar 2021
Size-Invariant Graph Representations for Graph Classification Extrapolations
International Conference on Machine Learning (ICML), 2021
Beatrice Bevilacqua
Yangze Zhou
Bruno Ribeiro
OOD
355
120
0
08 Mar 2021
Conditional Distributional Treatment Effect with Kernel Conditional Mean Embeddings and U-Statistic Regression
International Conference on Machine Learning (ICML), 2021
Junhyung Park
Uri Shalit
Bernhard Schölkopf
Krikamol Muandet
CML
275
41
0
16 Feb 2021
Shrinkage Bayesian Causal Forests for Heterogeneous Treatment Effects Estimation
Journal of Computational And Graphical Statistics (JCGS), 2021
A. Caron
G. Baio
I. Manolopoulou
CML
135
21
0
12 Feb 2021
Selecting Treatment Effects Models for Domain Adaptation Using Causal Knowledge
Trent Kyono
Ioana Bica
Zhaozhi Qian
Mihaela van der Schaar
OOD
CML
401
7
0
11 Feb 2021
Generating Synthetic Text Data to Evaluate Causal Inference Methods
Zach Wood-Doughty
I. Shpitser
Mark Dredze
SyDa
CML
202
12
0
10 Feb 2021
Grab the Reins of Crowds: Estimating the Effects of Crowd Movement Guidance Using Causal Inference
Adaptive Agents and Multi-Agent Systems (AAMAS), 2021
Koh Takeuchi
Ryo Nishida
Hisashi Kashima
Masaki Onishi
CML
109
4
0
08 Feb 2021
Learning Matching Representations for Individualized Organ Transplantation Allocation
International Conference on Artificial Intelligence and Statistics (AISTATS), 2021
Can Xu
Ahmed Alaa
Ioana Bica
B. Ershoff
M. Cannesson
M. Schaar
OOD
128
8
0
28 Jan 2021
Nonparametric Estimation of Heterogeneous Treatment Effects: From Theory to Learning Algorithms
International Conference on Artificial Intelligence and Statistics (AISTATS), 2021
Alicia Curth
M. Schaar
CML
323
177
0
26 Jan 2021
Estimating Average Treatment Effects via Orthogonal Regularization
International Conference on Information and Knowledge Management (CIKM), 2021
Tobias Hatt
Stefan Feuerriegel
CML
576
36
0
21 Jan 2021
Model Compression for Domain Adaptation through Causal Effect Estimation
Transactions of the Association for Computational Linguistics (TACL), 2021
Guy Rotman
Amir Feder
Roi Reichart
CML
250
8
0
18 Jan 2021
Intact-VAE: Estimating Treatment Effects under Unobserved Confounding
Pengzhou (Abel) Wu
Kenji Fukumizu
CML
257
13
0
17 Jan 2021
Fairness in Machine Learning
L. Oneto
Silvia Chiappa
FaML
674
534
0
31 Dec 2020
CAMTA: Causal Attention Model for Multi-touch Attribution
Sachin Kumar
Garima Gupta
Ranjitha Prasad
Arnab Chatterjee
Lovekesh Vig
Gautam M. Shroff
CML
HAI
188
15
0
21 Dec 2020
Fundamental Limits and Tradeoffs in Invariant Representation Learning
Journal of machine learning research (JMLR), 2020
Han Zhao
Chen Dan
Bryon Aragam
Tommi Jaakkola
Geoffrey J. Gordon
Pradeep Ravikumar
FaML
561
53
0
19 Dec 2020
Treatment Targeting by AUUC Maximization with Generalization Guarantees
Artem Betlei
Eustache Diemert
Massih-Reza Amini
CML
138
5
0
17 Dec 2020
Previous
1
2
3
4
5
6
7
8
9
Next
