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. 2201.00689
  4. Cited By
CausalMTA: Eliminating the User Confounding Bias for Causal Multi-touch
  Attribution

CausalMTA: Eliminating the User Confounding Bias for Causal Multi-touch Attribution

21 December 2021
Di Yao
Chang Gong
Lei Zhang
Sheng Chen
Jingping Bi
    CML
ArXivPDFHTML

Papers citing "CausalMTA: Eliminating the User Confounding Bias for Causal Multi-touch Attribution"

6 / 6 papers shown
Title
LiDDA: Data Driven Attribution at LinkedIn
LiDDA: Data Driven Attribution at LinkedIn
John Bencina
Erkut Aykutlug
Yue Chen
Zerui Zhang
Stephanie Sorenson
Shao Tang
Changshuai Wei
65
0
0
14 May 2025
Interpretable Deep Learning Model for Online Multi-touch Attribution
Interpretable Deep Learning Model for Online Multi-touch Attribution
Dongdong Yang
Kevin P. Dyer
Senzhang Wang
FAtt
18
10
0
26 Mar 2020
Attribution Modeling Increases Efficiency of Bidding in Display
  Advertising
Attribution Modeling Increases Efficiency of Bidding in Display Advertising
Eustache Diemert
Julien Meynet
Pierre Galland
Damien Lefortier
45
55
0
20 Jul 2017
Bayesian Inference of Individualized Treatment Effects using Multi-task
  Gaussian Processes
Bayesian Inference of Individualized Treatment Effects using Multi-task Gaussian Processes
Ahmed Alaa
M. Schaar
CML
170
302
0
10 Apr 2017
Learning Representations for Counterfactual Inference
Learning Representations for Counterfactual Inference
Fredrik D. Johansson
Uri Shalit
David Sontag
CML
OOD
BDL
280
729
0
12 May 2016
Variational Recurrent Auto-Encoders
Variational Recurrent Auto-Encoders
Otto Fabius
Joost R. van Amersfoort
GAN
BDL
DRL
86
248
0
20 Dec 2014
1