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1605.03661
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Learning Representations for Counterfactual Inference
12 May 2016
Fredrik D. Johansson
Uri Shalit
David Sontag
CML
OOD
BDL
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Papers citing
"Learning Representations for Counterfactual Inference"
50 / 432 papers shown
The Causal Learning of Retail Delinquency
AAAI Conference on Artificial Intelligence (AAAI), 2020
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Cheuk Hang Leung
Xing Yan
Qi Wu
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Zhixiang Huang
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177
9
0
17 Dec 2020
Causality-Aware Neighborhood Methods for Recommender Systems
European Conference on Information Retrieval (ECIR), 2020
Masahiro Sato
S. Takemori
Janmajay Singh
Qian Zhang
BDL
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139
7
0
17 Dec 2020
Proactive Pseudo-Intervention: Causally Informed Contrastive Learning For Interpretable Vision Models
Dong Wang
Yuewei Yang
Chenyang Tao
Zhe Gan
Liqun Chen
Fanjie Kong
Ricardo Henao
Lawrence Carin
266
0
0
06 Dec 2020
Balance Regularized Neural Network Models for Causal Effect Estimation
Mehrdad Farajtabar
Andrew Lee
Yuanjian Feng
Vishal Gupta
Peter Dolan
Harish Chandran
M. Szummer
CML
122
7
0
23 Nov 2020
Confounding Feature Acquisition for Causal Effect Estimation
Shirly Wang
S. Yi
Shalmali Joshi
Marzyeh Ghassemi
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133
2
0
17 Nov 2020
Causality-aware counterfactual confounding adjustment as an alternative to linear residualization in anticausal prediction tasks based on linear learners
E. C. Neto
OOD
CML
227
6
0
09 Nov 2020
Doubly Robust Off-Policy Learning on Low-Dimensional Manifolds by Deep Neural Networks
Minshuo Chen
Hao Liu
Wenjing Liao
T. Zhao
CML
OOD
OffRL
138
7
0
03 Nov 2020
Adapting Neural Networks for Uplift Models
Mouloud Belbahri
Olivier Gandouet
Ghaith Kazma
176
12
0
30 Oct 2020
DeepRite: Deep Recurrent Inverse TreatmEnt Weighting for Adjusting Time-varying Confounding in Modern Longitudinal Observational Data
Yanbo Xu
Cao Xiao
Jimeng Sun
BDL
OOD
CML
119
1
0
28 Oct 2020
Counterfactual Representation Learning with Balancing Weights
International Conference on Artificial Intelligence and Statistics (AISTATS), 2020
Serge Assaad
Shuxi Zeng
Chenyang Tao
Shounak Datta
Nikhil Mehta
Ricardo Henao
Fan Li
Lawrence Carin
CML
OOD
375
78
0
23 Oct 2020
Poincare: Recommending Publication Venues via Treatment Effect Estimation
Ryoma Sato
M. Yamada
H. Kashima
CML
183
2
0
19 Oct 2020
Double Robust Representation Learning for Counterfactual Prediction
Shuxi Zeng
Serge Assaad
Chenyang Tao
Shounak Datta
Lawrence Carin
Fan Li
OOD
CML
169
6
0
15 Oct 2020
GraphITE: Estimating Individual Effects of Graph-structured Treatments
Shonosuke Harada
H. Kashima
CML
225
28
0
29 Sep 2020
Learning from eXtreme Bandit Feedback
AAAI Conference on Artificial Intelligence (AAAI), 2020
Romain Lopez
Inderjit S. Dhillon
Sai Li
OffRL
191
26
0
27 Sep 2020
Adjusting for Confounders with Text: Challenges and an Empirical Evaluation Framework for Causal Inference
International Conference on Web and Social Media (ICWSM), 2020
Galen Cassebeer Weld
Peter West
M. Glenski
David Arbour
Ryan Rossi
Tim Althoff
CML
272
22
0
21 Sep 2020
Estimating Individual Treatment Effects using Non-Parametric Regression Models: a Review
A. Caron
G. Baio
I. Manolopoulou
CML
304
71
0
14 Sep 2020
Information Theoretic Counterfactual Learning from Missing-Not-At-Random Feedback
Neural Information Processing Systems (NeurIPS), 2020
Zifeng Wang
Xi Chen
Rui Wen
Shao-Lun Huang
E. Kuruoglu
Yefeng Zheng
BDL
CML
OffRL
224
90
0
06 Sep 2020
BLOB : A Probabilistic Model for Recommendation that Combines Organic and Bandit Signals
Knowledge Discovery and Data Mining (KDD), 2020
Otmane Sakhi
Stephen Bonner
D. Rohde
Flavian Vasile
199
37
0
28 Aug 2020
Estimating Individual Treatment Effects with Time-Varying Confounders
Industrial Conference on Data Mining (IDM), 2020
Ruoqi Liu
Changchang Yin
Ping Zhang
CML
195
32
0
27 Aug 2020
Hi-CI: Deep Causal Inference in High Dimensions
Ankit Sharma
Garima Gupta
Ranjitha Prasad
Arnab Chatterjee
Lovekesh Vig
Gautam M. Shroff
BDL
CML
234
4
0
22 Aug 2020
Long-Term Effect Estimation with Surrogate Representation
Lu Cheng
Ruocheng Guo
Huan Liu
CML
226
21
0
19 Aug 2020
Estimating Causal Effects with the Neural Autoregressive Density Estimator
Sergio Garrido
S. Borysov
Jeppe Rich
Francisco Câmara Pereira
CML
177
9
0
17 Aug 2020
On Learning Language-Invariant Representations for Universal Machine Translation
International Conference on Machine Learning (ICML), 2020
Hao Zhao
Junjie Hu
Andrej Risteski
189
8
0
11 Aug 2020
A Causal Lens for Peeking into Black Box Predictive Models: Predictive Model Interpretation via Causal Attribution
A. Khademi
Vasant Honavar
CML
131
9
0
01 Aug 2020
An Interpretable Probabilistic Approach for Demystifying Black-box Predictive Models
Catarina Moreira
Yu-Liang Chou
M. Velmurugan
Chun Ouyang
Prerna Agarwal
P. Bruza
224
65
0
21 Jul 2020
Causal Inference using Gaussian Processes with Structured Latent Confounders
International Conference on Machine Learning (ICML), 2020
Sam Witty
Kenta Takatsu
David D. Jensen
Vikash K. Mansinghka
CML
257
20
0
14 Jul 2020
A unified survey of treatment effect heterogeneity modeling and uplift modeling
ACM Computing Surveys (ACM CSUR), 2020
Weijia Zhang
Jiuyong Li
Lin Liu
CML
281
72
0
14 Jul 2020
On Linear Identifiability of Learned Representations
Geoffrey Roeder
Luke Metz
Diederik P. Kingma
CML
402
94
0
01 Jul 2020
Identifying Causal-Effect Inference Failure with Uncertainty-Aware Models
Andrew Jesson
Sören Mindermann
Uri Shalit
Y. Gal
CML
298
78
0
01 Jul 2020
Adversarial representation learning for synthetic replacement of private attributes
John Martinsson
Edvin Listo Zec
D. Gillblad
Olof Mogren
PICV
246
9
0
14 Jun 2020
Learning Decomposed Representation for Counterfactual Inference
Anpeng Wu
Kun Kuang
Junkun Yuan
Bo Li
Jianrong Tao
Qiang Zhu
Yueting Zhuang
Leilei Gan
CML
129
22
0
12 Jun 2020
Regret Minimization for Causal Inference on Large Treatment Space
International Conference on Artificial Intelligence and Statistics (AISTATS), 2020
Akira Tanimoto
Tomoya Sakai
Takashi Takenouchi
H. Kashima
CML
112
10
0
10 Jun 2020
Causality and Batch Reinforcement Learning: Complementary Approaches To Planning In Unknown Domains
James Bannon
Bradford T. Windsor
Wenbo Song
Tao Li
CML
OOD
OffRL
157
22
0
03 Jun 2020
CausaLM: Causal Model Explanation Through Counterfactual Language Models
International Conference on Computational Logic (ICCL), 2020
Amir Feder
Nadav Oved
Uri Shalit
Roi Reichart
CML
LRM
562
179
0
27 May 2020
Counterfactual Propagation for Semi-Supervised Individual Treatment Effect Estimation
Shonosuke Harada
H. Kashima
CML
96
4
0
11 May 2020
Text and Causal Inference: A Review of Using Text to Remove Confounding from Causal Estimates
Annual Meeting of the Association for Computational Linguistics (ACL), 2020
Katherine A. Keith
David D. Jensen
Brendan O'Connor
CML
212
127
0
01 May 2020
MultiMBNN: Matched and Balanced Causal Inference with Neural Networks
The European Symposium on Artificial Neural Networks (ESANN), 2020
Ankit Sharma
Garima Gupta
Ranjitha Prasad
Arnab Chatterjee
Lovekesh Vig
Gautam M. Shroff
CML
169
8
0
28 Apr 2020
Learning Continuous Treatment Policy and Bipartite Embeddings for Matching with Heterogeneous Causal Effects
Will Y. Zou
S. Shyam
Michael Mui
Mingshi Wang
Jan Pedersen
Zoubin Ghahramani
CML
159
2
0
21 Apr 2020
Causality-aware counterfactual confounding adjustment for feature representations learned by deep models
E. C. Neto
AI4CE
OOD
BDL
CML
199
2
0
20 Apr 2020
Estimating Individual Treatment Effects through Causal Populations Identification
The European Symposium on Artificial Neural Networks (ESANN), 2020
Céline Beji
Michaël Bon
Florian Yger
Jamal Atif
CML
239
3
0
10 Apr 2020
Learning Latent Causal Structures with a Redundant Input Neural Network
Jonathan D. Young
Bryan Andrews
G. Cooper
Xinghua Lu
CML
193
10
0
29 Mar 2020
ParKCa: Causal Inference with Partially Known Causes
Pacific Symposium on Biocomputing (PSB), 2020
Raquel Y. S. Aoki
Martin Ester
CML
207
6
0
17 Mar 2020
Optimizing Medical Treatment for Sepsis in Intensive Care: from Reinforcement Learning to Pre-Trial Evaluation
Luchen Li
I. Albert-Smet
Aldo A. Faisal
OffRL
142
12
0
13 Mar 2020
Adversarial Machine Learning: Bayesian Perspectives
Journal of the American Statistical Association (JASA), 2020
D. Insua
Roi Naveiro
Víctor Gallego
Jason Poulos
AAML
163
31
0
07 Mar 2020
Estimating the Effects of Continuous-valued Interventions using Generative Adversarial Networks
Neural Information Processing Systems (NeurIPS), 2020
Ioana Bica
James Jordon
M. Schaar
CML
286
116
0
27 Feb 2020
Off-Policy Evaluation and Learning for External Validity under a Covariate Shift
Neural Information Processing Systems (NeurIPS), 2020
Masahiro Kato
Masatoshi Uehara
Shota Yasui
OffRL
206
56
0
26 Feb 2020
MissDeepCausal: Causal Inference from Incomplete Data Using Deep Latent Variable Models
Imke Mayer
Julie Josse
Félix Raimundo
Jean-Philippe Vert
CML
144
13
0
25 Feb 2020
Causal Inference under Networked Interference and Intervention Policy Enhancement
International Conference on Artificial Intelligence and Statistics (AISTATS), 2020
Yunpu Ma
Volker Tresp
CML
165
48
0
20 Feb 2020
Estimating Counterfactual Treatment Outcomes over Time Through Adversarially Balanced Representations
International Conference on Learning Representations (ICLR), 2020
Ioana Bica
Ahmed Alaa
James Jordon
M. Schaar
BDL
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219
209
0
10 Feb 2020
A Survey on Causal Inference
ACM Transactions on Knowledge Discovery from Data (TKDD), 2020
Liuyi Yao
Zhixuan Chu
Sheng Li
Yaliang Li
Jing Gao
Aidong Zhang
CML
283
612
0
05 Feb 2020
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