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2203.09672
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Deep Multi-Modal Structural Equations For Causal Effect Estimation With Unstructured Proxies
Neural Information Processing Systems (NeurIPS), 2022
18 March 2022
Shachi Deshpande
Kaiwen Wang
Dhruv Sreenivas
Zheng Li
Volodymyr Kuleshov
CML
SyDa
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Papers citing
"Deep Multi-Modal Structural Equations For Causal Effect Estimation With Unstructured Proxies"
37 / 37 papers shown
LLM-Driven Treatment Effect Estimation Under Inference Time Text Confounding
Yuchen Ma
Dennis Frauen
Jonas Schweisthal
Stefan Feuerriegel
CML
205
3
0
03 Jul 2025
Causal Prompt Calibration Guided Segment Anything Model for Open-Vocabulary Multi-Entity Segmentation
Wenwen Qiang
Jianqi Zhang
Jingyao Wang
Changwen Zheng
VLM
374
0
0
10 May 2025
Simple and Effective Masked Diffusion Language Models
Subham Sekhar Sahoo
Marianne Arriola
Yair Schiff
Aaron Gokaslan
Edgar Marroquin
Justin T Chiu
Alexander M. Rush
Volodymyr Kuleshov
DiffM
273
376
0
11 Jun 2024
Recovering Latent Confounders from High-dimensional Proxy Variables
Nathan Mankovich
Homer Durand
Emiliano Díaz
Gherardo Varando
Gustau Camps-Valls
171
1
0
21 Mar 2024
Denoising Diffusion Variational Inference: Diffusion Models as Expressive Variational Posteriors
Wasu Top Piriyakulkij
Yingheng Wang
Volodymyr Kuleshov
DiffM
434
2
0
05 Jan 2024
Diffusion Models With Learned Adaptive Noise
Subham Sekhar Sahoo
Aaron Gokaslan
Christopher De Sa
Volodymyr Kuleshov
DiffM
372
38
0
20 Dec 2023
ViStruct: Visual Structural Knowledge Extraction via Curriculum Guided Code-Vision Representation
Conference on Empirical Methods in Natural Language Processing (EMNLP), 2023
Yangyi Chen
Xingyao Wang
Pengfei Yu
Derek Hoiem
Heng Ji
252
14
0
22 Nov 2023
Calibrated and Conformal Propensity Scores for Causal Effect Estimation
Conference on Uncertainty in Artificial Intelligence (UAI), 2023
Shachi Deshpande
Volodymyr Kuleshov
CML
338
1
0
01 Jun 2023
Patchwork Learning: A Paradigm Towards Integrative Analysis across Diverse Biomedical Data Sources
Patterns (Patterns), 2023
Suraj Rajendran
Weishen Pan
M. Sabuncu
Yong Chen
Jiayu Zhou
Fei Wang
265
24
0
10 May 2023
Estimating Causal Effects using a Multi-task Deep Ensemble
International Conference on Machine Learning (ICML), 2023
Ziyang Jiang
Zhuoran Hou
Yi-Ling Liu
Yiman Ren
Keyu Li
David Carlson
CML
298
7
0
26 Jan 2023
Deep Causal Learning: Representation, Discovery and Inference
Zizhen Deng
Xiaolong Zheng
Hu Tian
D. Zeng
CML
BDL
337
17
0
07 Nov 2022
CLIP-Event: Connecting Text and Images with Event Structures
Computer Vision and Pattern Recognition (CVPR), 2022
Pengfei Yu
Ruochen Xu
Shuohang Wang
Luowei Zhou
Xudong Lin
Chenguang Zhu
Michael Zeng
Heng Ji
Shih-Fu Chang
VLM
CLIP
192
145
0
13 Jan 2022
Towards Principled Causal Effect Estimation by Deep Identifiable Models
Pengzhou (Abel) Wu
Kenji Fukumizu
BDL
OOD
CML
262
3
0
30 Sep 2021
The Causal-Neural Connection: Expressiveness, Learnability, and Inference
K. Xia
Kai-Zhan Lee
Yoshua Bengio
Elias Bareinboim
CML
357
131
0
02 Jul 2021
Towards Causal Representation Learning
Bernhard Schölkopf
Francesco Locatello
Stefan Bauer
Nan Rosemary Ke
Nal Kalchbrenner
Anirudh Goyal
Yoshua Bengio
OOD
CML
AI4CE
357
345
0
22 Feb 2021
Counterfactual Fairness with Disentangled Causal Effect Variational Autoencoder
AAAI Conference on Artificial Intelligence (AAAI), 2020
Hyemi Kim
Seungjae Shin
Joonho Jang
Kyungwoo Song
Weonyoung Joo
Wanmo Kang
Il-Chul Moon
BDL
CML
277
65
0
24 Nov 2020
Causal Effects of Linguistic Properties
North American Chapter of the Association for Computational Linguistics (NAACL), 2020
Reid Pryzant
Dallas Card
Dan Jurafsky
Victor Veitch
Dhanya Sridhar
CML
365
53
0
24 Oct 2020
Targeted VAE: Variational and Targeted Learning for Causal Inference
M. Vowels
Necati Cihan Camgöz
Richard Bowden
BDL
OOD
CML
312
9
0
28 Sep 2020
Deep Structural Causal Models for Tractable Counterfactual Inference
Neural Information Processing Systems (NeurIPS), 2020
Nick Pawlowski
Daniel Coelho De Castro
Ben Glocker
CML
MedIm
386
287
0
11 Jun 2020
MissDeepCausal: Causal Inference from Incomplete Data Using Deep Latent Variable Models
Imke Mayer
Julie Josse
Félix Raimundo
Jean-Philippe Vert
CML
151
13
0
25 Feb 2020
Decision-Making with Auto-Encoding Variational Bayes
Neural Information Processing Systems (NeurIPS), 2020
Romain Lopez
Pierre Boyeau
Nir Yosef
Michael I. Jordan
Jeffrey Regier
BDL
1.5K
20,656
0
17 Feb 2020
Treatment effect estimation with disentangled latent factors
AAAI Conference on Artificial Intelligence (AAAI), 2020
Weijia Zhang
Lin Liu
Jiuyong Li
CML
217
106
0
29 Jan 2020
Adapting Neural Networks for the Estimation of Treatment Effects
Neural Information Processing Systems (NeurIPS), 2019
Claudia Shi
David M. Blei
Victor Veitch
CML
530
452
0
05 Jun 2019
Support and Invertibility in Domain-Invariant Representations
Fredrik D. Johansson
David Sontag
Rajesh Ranganath
408
172
0
08 Mar 2019
Using Embeddings to Correct for Unobserved Confounding in Networks
Neural Information Processing Systems (NeurIPS), 2019
Victor Veitch
Yixin Wang
David M. Blei
CML
234
61
0
11 Feb 2019
The Blessings of Multiple Causes
Yixin Wang
David M. Blei
AI4CE
CML
303
309
0
17 May 2018
Learning Weighted Representations for Generalization Across Designs
Fredrik D. Johansson
Nathan Kallus
Uri Shalit
David Sontag
OOD
242
91
0
23 Feb 2018
DeepMatch: Balancing Deep Covariate Representations for Causal Inference Using Adversarial Training
Nathan Kallus
CML
OOD
221
83
0
15 Feb 2018
Multimodal Generative Models for Scalable Weakly-Supervised Learning
Mike Wu
Noah D. Goodman
DRL
338
441
0
14 Feb 2018
UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction
Leland McInnes
John Healy
James Melville
1.0K
11,410
0
09 Feb 2018
How to Make Causal Inferences Using Texts
Naoki Egami
Christian Fong
Justin Grimmer
Margaret E. Roberts
Brandon M Stewart
CML
262
167
0
06 Feb 2018
Implicit Causal Models for Genome-wide Association Studies
International Conference on Learning Representations (ICLR), 2017
Dustin Tran
David M. Blei
CML
97
45
0
30 Oct 2017
Causal Effect Inference with Deep Latent-Variable Models
Christos Louizos
Uri Shalit
Joris Mooij
David Sontag
R. Zemel
Max Welling
CML
BDL
467
836
0
24 May 2017
Age Progression/Regression by Conditional Adversarial Autoencoder
Computer Vision and Pattern Recognition (CVPR), 2017
Zhifei Zhang
Yang Song
Hairong Qi
GAN
CVBM
316
1,233
0
27 Feb 2017
Counterfactual Prediction with Deep Instrumental Variables Networks
Jason S. Hartford
Greg Lewis
Kevin Leyton-Brown
Matt Taddy
CML
OOD
327
49
0
30 Dec 2016
Learning Representations for Counterfactual Inference
Fredrik D. Johansson
Uri Shalit
David Sontag
CML
OOD
BDL
832
795
0
12 May 2016
Variational Inference: A Review for Statisticians
David M. Blei
A. Kucukelbir
Jon D. McAuliffe
BDL
1.7K
5,377
0
04 Jan 2016
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