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. 2310.06100
  4. Cited By
High Dimensional Causal Inference with Variational Backdoor Adjustment

High Dimensional Causal Inference with Variational Backdoor Adjustment

9 October 2023
Daniel Israel
Aditya Grover
Guy Van den Broeck
    CML
ArXivPDFHTML

Papers citing "High Dimensional Causal Inference with Variational Backdoor Adjustment"

13 / 13 papers shown
Title
A Neural Mean Embedding Approach for Back-door and Front-door Adjustment
A Neural Mean Embedding Approach for Back-door and Front-door Adjustment
Liyuan Xu
Arthur Gretton
CML
BDL
42
8
0
12 Oct 2022
MedMNIST v2 -- A large-scale lightweight benchmark for 2D and 3D
  biomedical image classification
MedMNIST v2 -- A large-scale lightweight benchmark for 2D and 3D biomedical image classification
Jiancheng Yang
Rui Shi
D. Wei
Zequan Liu
Lin Zhao
B. Ke
Hanspeter Pfister
Bingbing Ni
VLM
290
697
0
27 Oct 2021
Interpolating between sampling and variational inference with infinite
  stochastic mixtures
Interpolating between sampling and variational inference with infinite stochastic mixtures
Richard D. Lange
Ari S. Benjamin
Ralf M. Haefner
Xaq Pitkow
29
7
0
18 Oct 2021
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
147
28
0
12 Feb 2021
Intact-VAE: Estimating Treatment Effects under Unobserved Confounding
Intact-VAE: Estimating Treatment Effects under Unobserved Confounding
Pengzhou (Abel) Wu
Kenji Fukumizu
CML
49
13
0
17 Jan 2021
Decision-Making with Auto-Encoding Variational Bayes
Decision-Making with Auto-Encoding Variational Bayes
Romain Lopez
Pierre Boyeau
Nir Yosef
Michael I. Jordan
Jeffrey Regier
BDL
380
10,591
0
17 Feb 2020
Treatment effect estimation with disentangled latent factors
Treatment effect estimation with disentangled latent factors
Weijia Zhang
Lin Liu
Jiuyong Li
CML
43
89
0
29 Jan 2020
Variational Autoencoders and Nonlinear ICA: A Unifying Framework
Variational Autoencoders and Nonlinear ICA: A Unifying Framework
Ilyes Khemakhem
Diederik P. Kingma
Ricardo Pio Monti
Aapo Hyvarinen
OOD
68
594
0
10 Jul 2019
Adapting Neural Networks for the Estimation of Treatment Effects
Adapting Neural Networks for the Estimation of Treatment Effects
Claudia Shi
David M. Blei
Victor Veitch
CML
145
374
0
05 Jun 2019
Challenging Common Assumptions in the Unsupervised Learning of
  Disentangled Representations
Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations
Francesco Locatello
Stefan Bauer
Mario Lucic
Gunnar Rätsch
Sylvain Gelly
Bernhard Schölkopf
Olivier Bachem
OOD
115
1,466
0
29 Nov 2018
FFJORD: Free-form Continuous Dynamics for Scalable Reversible Generative
  Models
FFJORD: Free-form Continuous Dynamics for Scalable Reversible Generative Models
Will Grathwohl
Ricky T. Q. Chen
J. Bettencourt
Ilya Sutskever
David Duvenaud
DRL
134
873
0
02 Oct 2018
Categorical Reparameterization with Gumbel-Softmax
Categorical Reparameterization with Gumbel-Softmax
Eric Jang
S. Gu
Ben Poole
BDL
305
5,364
0
03 Nov 2016
Variational Inference with Normalizing Flows
Variational Inference with Normalizing Flows
Danilo Jimenez Rezende
S. Mohamed
DRL
BDL
308
4,175
0
21 May 2015
1