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Compositional Models for Estimating Causal Effects
v1v2v3 (latest)

Compositional Models for Estimating Causal Effects

25 June 2024
Purva Pruthi
David D. Jensen
    CML
ArXiv (abs)PDFHTML

Papers citing "Compositional Models for Estimating Causal Effects"

32 / 32 papers shown
Title
On The Specialization of Neural Modules
On The Specialization of Neural Modules
Devon Jarvis
Richard Klein
Benjamin Rosman
Andrew M. Saxe
114
14
0
23 Sep 2024
Breaking Neural Network Scaling Laws with Modularity
Breaking Neural Network Scaling Laws with Modularity
Akhilan Boopathy
Sunshine Jiang
William Yue
Jaedong Hwang
Abhiram Iyer
Ila Fiete
OOD
115
2
0
09 Sep 2024
What makes Models Compositional? A Theoretical View: With Supplement
What makes Models Compositional? A Theoretical View: With Supplement
Parikshit Ram
Tim Klinger
Alexander G. Gray
CoGe
62
6
0
02 May 2024
Hierarchical Causal Models
Hierarchical Causal Models
Eli N. Weinstein
David M. Blei
CML
35
3
0
10 Jan 2024
Discovering modular solutions that generalize compositionally
Discovering modular solutions that generalize compositionally
Simon Schug
Seijin Kobayashi
Yassir Akram
Maciej Wolczyk
Alexandra Proca
J. Oswald
Razvan Pascanu
João Sacramento
Angelika Steger
49
15
0
22 Dec 2023
ExeDec: Execution Decomposition for Compositional Generalization in
  Neural Program Synthesis
ExeDec: Execution Decomposition for Compositional Generalization in Neural Program Synthesis
Kensen Shi
Joey Hong
Yinlin Deng
Pengcheng Yin
Manzil Zaheer
Charles Sutton
56
19
0
26 Jul 2023
Compositional Generalization from First Principles
Compositional Generalization from First Principles
Thaddäus Wiedemer
Prasanna Mayilvahanan
Matthias Bethge
Wieland Brendel
OCL
81
46
0
10 Jul 2023
Modular Deep Learning
Modular Deep Learning
Jonas Pfeiffer
Sebastian Ruder
Ivan Vulić
Edoardo Ponti
MoMeOOD
139
79
0
22 Feb 2023
Learning Relational Causal Models with Cycles through Relational
  Acyclification
Learning Relational Causal Models with Cycles through Relational Acyclification
Ragib Ahsan
David Arbour
Elena Zheleva
44
2
0
25 Aug 2022
Image-based Treatment Effect Heterogeneity
Image-based Treatment Effect Heterogeneity
Connor Jerzak
Fredrik D. Johansson
Adel Daoud
89
22
0
13 Jun 2022
Is a Modular Architecture Enough?
Is a Modular Architecture Enough?
Sarthak Mittal
Yoshua Bengio
Guillaume Lajoie
105
48
0
06 Jun 2022
Causal Effect Inference for Structured Treatments
Causal Effect Inference for Structured Treatments
Jean Kaddour
Yuchen Zhu
Qi Liu
Matt J. Kusner
Ricardo M. A. Silva
CML
229
50
0
03 Jun 2021
Nonparametric Estimation of Heterogeneous Treatment Effects: From Theory
  to Learning Algorithms
Nonparametric Estimation of Heterogeneous Treatment Effects: From Theory to Learning Algorithms
Alicia Curth
M. Schaar
CML
163
149
0
26 Jan 2021
How and Why to Use Experimental Data to Evaluate Methods for
  Observational Causal Inference
How and Why to Use Experimental Data to Evaluate Methods for Observational Causal Inference
A. Gentzel
Purva Pruthi
David D. Jensen
CML
58
18
0
06 Oct 2020
GraphITE: Estimating Individual Effects of Graph-structured Treatments
GraphITE: Estimating Individual Effects of Graph-structured Treatments
Shonosuke Harada
H. Kashima
CML
66
23
0
29 Sep 2020
Towards optimal doubly robust estimation of heterogeneous causal effects
Towards optimal doubly robust estimation of heterogeneous causal effects
Edward H. Kennedy
CML
168
326
0
29 Apr 2020
Causal Relational Learning
Causal Relational Learning
Babak Salimi
Harsh Parikh
Moe Kayali
Sudeepa Roy
Lise Getoor
Dan Suciu
CML
34
44
0
07 Apr 2020
Generalization Bounds and Representation Learning for Estimation of
  Potential Outcomes and Causal Effects
Generalization Bounds and Representation Learning for Estimation of Potential Outcomes and Causal Effects
Fredrik D. Johansson
Uri Shalit
Nathan Kallus
David Sontag
CMLOOD
78
100
0
21 Jan 2020
Compositionality decomposed: how do neural networks generalise?
Compositionality decomposed: how do neural networks generalise?
Dieuwke Hupkes
Verna Dankers
Mathijs Mul
Elia Bruni
CoGe
152
338
0
22 Aug 2019
MCP: Learning Composable Hierarchical Control with Multiplicative
  Compositional Policies
MCP: Learning Composable Hierarchical Control with Multiplicative Compositional Policies
Xue Bin Peng
Michael Chang
Grace Zhang
Pieter Abbeel
Sergey Levine
74
197
0
23 May 2019
Overlap in Observational Studies with High-Dimensional Covariates
Overlap in Observational Studies with High-Dimensional Covariates
Alexander DÁmour
Peng Ding
Avi Feller
Lihua Lei
Jasjeet Sekhon
149
195
0
07 Nov 2017
Meta-learners for Estimating Heterogeneous Treatment Effects using
  Machine Learning
Meta-learners for Estimating Heterogeneous Treatment Effects using Machine Learning
Sören R. Künzel
Jasjeet Sekhon
Peter J. Bickel
Bin Yu
CML
164
928
0
12 Jun 2017
Outrageously Large Neural Networks: The Sparsely-Gated
  Mixture-of-Experts Layer
Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer
Noam M. Shazeer
Azalia Mirhoseini
Krzysztof Maziarz
Andy Davis
Quoc V. Le
Geoffrey E. Hinton
J. Dean
MoE
253
2,683
0
23 Jan 2017
Learning Representations for Counterfactual Inference
Learning Representations for Counterfactual Inference
Fredrik D. Johansson
Uri Shalit
David Sontag
CMLOODBDL
282
729
0
12 May 2016
Neural Module Networks
Neural Module Networks
Jacob Andreas
Marcus Rohrbach
Trevor Darrell
Dan Klein
CoGe
139
1,076
0
09 Nov 2015
Estimation and Inference of Heterogeneous Treatment Effects using Random
  Forests
Estimation and Inference of Heterogeneous Treatment Effects using Random Forests
Stefan Wager
Susan Athey
SyDaCML
354
2,490
0
14 Oct 2015
Recursive Partitioning for Heterogeneous Causal Effects
Recursive Partitioning for Heterogeneous Causal Effects
Susan Athey
Guido Imbens
CML
262
1,436
0
05 Apr 2015
Improved Semantic Representations From Tree-Structured Long Short-Term
  Memory Networks
Improved Semantic Representations From Tree-Structured Long Short-Term Memory Networks
Kai Sheng Tai
R. Socher
Christopher D. Manning
AIMat
142
3,122
0
28 Feb 2015
A Sound and Complete Algorithm for Learning Causal Models from
  Relational Data
A Sound and Complete Algorithm for Learning Causal Models from Relational Data
Marc E. Maier
Katerina Marazopoulou
David Arbour
David D. Jensen
CML
74
57
0
26 Sep 2013
Object-Oriented Bayesian Networks
Object-Oriented Bayesian Networks
D. Koller
Avi Pfeffer
UQCV
122
632
0
06 Feb 2013
Counterfactual Reasoning and Learning Systems
Counterfactual Reasoning and Learning Systems
Léon Bottou
J. Peters
J. Q. Candela
Denis Xavier Charles
D. M. Chickering
Elon Portugaly
Dipankar Ray
Patrice Y. Simard
Edward Snelson
CMLOffRL
387
786
0
11 Sep 2012
A Contextual-Bandit Approach to Personalized News Article Recommendation
A Contextual-Bandit Approach to Personalized News Article Recommendation
Lihong Li
Wei Chu
John Langford
Robert Schapire
471
2,955
0
28 Feb 2010
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