ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2002.10837
  4. Cited By
MissDeepCausal: Causal Inference from Incomplete Data Using Deep Latent
  Variable Models

MissDeepCausal: Causal Inference from Incomplete Data Using Deep Latent Variable Models

25 February 2020
Imke Mayer
Julie Josse
Félix Raimundo
Jean-Philippe Vert
    CML
ArXivPDFHTML

Papers citing "MissDeepCausal: Causal Inference from Incomplete Data Using Deep Latent Variable Models"

4 / 4 papers shown
Title
Deep Multi-Modal Structural Equations For Causal Effect Estimation With
  Unstructured Proxies
Deep Multi-Modal Structural Equations For Causal Effect Estimation With Unstructured Proxies
Shachi Deshpande
Kaiwen Wang
Dhruv Sreenivas
Zheng Li
Volodymyr Kuleshov
CML
SyDa
16
11
0
18 Mar 2022
A Critical Look at the Consistency of Causal Estimation With Deep Latent
  Variable Models
A Critical Look at the Consistency of Causal Estimation With Deep Latent Variable Models
Severi Rissanen
Pekka Marttinen
CML
20
26
0
12 Feb 2021
Causal Discovery from Incomplete Data using An Encoder and Reinforcement
  Learning
Causal Discovery from Incomplete Data using An Encoder and Reinforcement Learning
Xiaoshui Huang
Fujin Zhu
Lois Holloway
Ali Haidar
CML
14
10
0
09 Jun 2020
Learning Representations for Counterfactual Inference
Learning Representations for Counterfactual Inference
Fredrik D. Johansson
Uri Shalit
David Sontag
CML
OOD
BDL
232
719
0
12 May 2016
1