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Deep Multi-Modal Structural Equations For Causal Effect Estimation With
  Unstructured Proxies

Deep Multi-Modal Structural Equations For Causal Effect Estimation With Unstructured Proxies

18 March 2022
Shachi Deshpande
Kaiwen Wang
Dhruv Sreenivas
Zheng Li
Volodymyr Kuleshov
    CML
    SyDa
ArXivPDFHTML

Papers citing "Deep Multi-Modal Structural Equations For Causal Effect Estimation With Unstructured Proxies"

11 / 11 papers shown
Title
Causal Prompt Calibration Guided Segment Anything Model for Open-Vocabulary Multi-Entity Segmentation
Causal Prompt Calibration Guided Segment Anything Model for Open-Vocabulary Multi-Entity Segmentation
Wenwen Qiang
Jianqi Zhang
Jingyao Wang
Changwen Zheng
VLM
37
0
0
10 May 2025
Recovering Latent Confounders from High-dimensional Proxy Variables
Recovering Latent Confounders from High-dimensional Proxy Variables
Nathan Mankovich
Homer Durand
Emiliano Díaz
Gherardo Varando
Gustau Camps-Valls
22
0
0
21 Mar 2024
Denoising Diffusion Variational Inference: Diffusion Models as Expressive Variational Posteriors
Denoising Diffusion Variational Inference: Diffusion Models as Expressive Variational Posteriors
Wasu Top Piriyakulkij
Yingheng Wang
Volodymyr Kuleshov
DiffM
37
1
0
05 Jan 2024
Diffusion Models With Learned Adaptive Noise
Diffusion Models With Learned Adaptive Noise
S. Sahoo
Aaron Gokaslan
Christopher De Sa
Volodymyr Kuleshov
DiffM
34
8
0
20 Dec 2023
ViStruct: Visual Structural Knowledge Extraction via Curriculum Guided
  Code-Vision Representation
ViStruct: Visual Structural Knowledge Extraction via Curriculum Guided Code-Vision Representation
Yangyi Chen
Xingyao Wang
Manling Li
Derek Hoiem
Heng Ji
30
11
0
22 Nov 2023
Calibrated and Conformal Propensity Scores for Causal Effect Estimation
Calibrated and Conformal Propensity Scores for Causal Effect Estimation
Shachi Deshpande
Volodymyr Kuleshov
CML
16
1
0
01 Jun 2023
Patchwork Learning: A Paradigm Towards Integrative Analysis across
  Diverse Biomedical Data Sources
Patchwork Learning: A Paradigm Towards Integrative Analysis across Diverse Biomedical Data Sources
Suraj Rajendran
Weishen Pan
M. Sabuncu
Yong Chen
Jiayu Zhou
Fei Wang
54
14
0
10 May 2023
Estimating Causal Effects using a Multi-task Deep Ensemble
Estimating Causal Effects using a Multi-task Deep Ensemble
Ziyang Jiang
Zhuoran Hou
Yi-Ling Liu
Yiman Ren
Keyu Li
David Carlson
CML
24
6
0
26 Jan 2023
Deep Causal Learning: Representation, Discovery and Inference
Deep Causal Learning: Representation, Discovery and Inference
Zizhen Deng
Xiaolong Zheng
Hu Tian
D. Zeng
CML
BDL
36
11
0
07 Nov 2022
Towards Principled Causal Effect Estimation by Deep Identifiable Models
Towards Principled Causal Effect Estimation by Deep Identifiable Models
Pengzhou (Abel) Wu
Kenji Fukumizu
BDL
OOD
CML
27
3
0
30 Sep 2021
Learning Representations for Counterfactual Inference
Learning Representations for Counterfactual Inference
Fredrik D. Johansson
Uri Shalit
David Sontag
CML
OOD
BDL
229
719
0
12 May 2016
1