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Budgeted Experiment Design for Causal Structure Learning
v1v2 (latest)

Budgeted Experiment Design for Causal Structure Learning

11 September 2017
AmirEmad Ghassami
Saber Salehkaleybar
Negar Kiyavash
Elias Bareinboim
    CML
ArXiv (abs)PDFHTML

Papers citing "Budgeted Experiment Design for Causal Structure Learning"

32 / 32 papers shown
Title
Characterization and Learning of Causal Graphs from Hard Interventions
Characterization and Learning of Causal Graphs from Hard Interventions
Zihan Zhou
Muhammad Qasim Elahi
Murat Kocaoglu
CML
136
0
0
02 May 2025
New metrics and search algorithms for weighted causal DAGs
New metrics and search algorithms for weighted causal DAGs
Davin Choo
Kirankumar Shiragur
CML
72
1
0
08 May 2023
Causal Discovery and Optimal Experimental Design for Genome-Scale
  Biological Network Recovery
Causal Discovery and Optimal Experimental Design for Genome-Scale Biological Network Recovery
Ashka Shah
A. Ramanathan
Valérie Hayot-Sasson
Rick L. Stevens
CML
29
1
0
06 Apr 2023
Subset verification and search algorithms for causal DAGs
Subset verification and search algorithms for causal DAGs
Davin Choo
Kirankumar Shiragur
CML
56
11
0
09 Jan 2023
Trust Your $\nabla$: Gradient-based Intervention Targeting for Causal
  Discovery
Trust Your ∇\nabla∇: Gradient-based Intervention Targeting for Causal Discovery
Mateusz Olko
Michal Zajac
A. Nowak
Nino Scherrer
Yashas Annadani
Stefan Bauer
Lukasz Kucinski
Piotr Milos
CML
138
2
0
24 Nov 2022
Sample Constrained Treatment Effect Estimation
Sample Constrained Treatment Effect Estimation
Raghavendra Addanki
David Arbour
Tung Mai
Cameron Musco
Anup B. Rao
49
7
0
12 Oct 2022
Neural Design for Genetic Perturbation Experiments
Neural Design for Genetic Perturbation Experiments
Aldo Pacchiano
Drausin Wulsin
Robert A. Barton
L. Voloch
80
5
0
26 Jul 2022
Verification and search algorithms for causal DAGs
Verification and search algorithms for causal DAGs
Davin Choo
Kirankumar Shiragur
Arnab Bhattacharyya
CML
55
12
0
30 Jun 2022
Causal Structure Learning: a Combinatorial Perspective
Causal Structure Learning: a Combinatorial Perspective
C. Squires
Caroline Uhler
CML
126
47
0
02 Jun 2022
A Unified Experiment Design Approach for Cyclic and Acyclic Causal
  Models
A Unified Experiment Design Approach for Cyclic and Acyclic Causal Models
Ehsan Mokhtarian
Saber Salehkaleybar
AmirEmad Ghassami
Negar Kiyavash
97
3
0
20 May 2022
Polynomial-Time Algorithms for Counting and Sampling Markov Equivalent
  DAGs with Applications
Polynomial-Time Algorithms for Counting and Sampling Markov Equivalent DAGs with Applications
Marcel Wienöbst
Max Bannach
Maciej Liskiewicz
61
10
0
05 May 2022
Experimental Design for Causal Effect Identification
Experimental Design for Causal Effect Identification
S. Akbari
Jalal Etesami
Negar Kiyavash
CML
64
1
0
04 May 2022
Provably Efficient Causal Model-Based Reinforcement Learning for
  Systematic Generalization
Provably Efficient Causal Model-Based Reinforcement Learning for Systematic Generalization
Mirco Mutti
Ric De Santi
Emanuele Rossi
J. Calderón
Michael M. Bronstein
Marcello Restelli
113
14
0
14 Feb 2022
Universal Lower Bound for Learning Causal DAGs with Atomic Interventions
Universal Lower Bound for Learning Causal DAGs with Atomic Interventions
Vibhor Porwal
P. Srivastava
Gaurav Sinha
CML
96
2
0
09 Nov 2021
ParaLiNGAM: Parallel Causal Structure Learning for Linear non-Gaussian
  Acyclic Models
ParaLiNGAM: Parallel Causal Structure Learning for Linear non-Gaussian Acyclic Models
Amirhossein Shahbazinia
Saber Salehkaleybar
Matin Hashemi
CML
90
8
0
28 Sep 2021
Learning Neural Causal Models with Active Interventions
Learning Neural Causal Models with Active Interventions
Nino Scherrer
O. Bilaniuk
Yashas Annadani
Anirudh Goyal
Patrick Schwab
Bernhard Schölkopf
Michael C. Mozer
Yoshua Bengio
Stefan Bauer
Nan Rosemary Ke
CML
125
44
0
06 Sep 2021
Matching a Desired Causal State via Shift Interventions
Matching a Desired Causal State via Shift Interventions
Jiaqi Zhang
C. Squires
Caroline Uhler
95
16
0
05 Jul 2021
Collaborative Causal Discovery with Atomic Interventions
Collaborative Causal Discovery with Atomic Interventions
Raghavendra Addanki
S. Kasiviswanathan
91
4
0
06 Jun 2021
Near-Optimal Multi-Perturbation Experimental Design for Causal Structure
  Learning
Near-Optimal Multi-Perturbation Experimental Design for Causal Structure Learning
Scott Sussex
Andreas Krause
Caroline Uhler
CML
94
20
0
28 May 2021
Active Structure Learning of Causal DAGs via Directed Clique Tree
Active Structure Learning of Causal DAGs via Directed Clique Tree
C. Squires
Sara Magliacane
Kristjan Greenewald
Dmitriy A. Katz
Murat Kocaoglu
Karthikeyan Shanmugam
CML
126
34
0
01 Nov 2020
Causal learning with sufficient statistics: an information bottleneck
  approach
Causal learning with sufficient statistics: an information bottleneck approach
D. Chicharro
M. Besserve
S. Panzeri
CML
65
5
0
12 Oct 2020
Active Learning of Causal Structures with Deep Reinforcement Learning
Active Learning of Causal Structures with Deep Reinforcement Learning
Amir Amirinezhad
Saber Salehkaleybar
Matin Hashemi
CML
74
12
0
07 Sep 2020
Causal Discovery in Physical Systems from Videos
Causal Discovery in Physical Systems from Videos
Yunzhu Li
Antonio Torralba
Anima Anandkumar
Dieter Fox
Animesh Garg
CML
124
104
0
01 Jul 2020
LazyIter: A Fast Algorithm for Counting Markov Equivalent DAGs and
  Designing Experiments
LazyIter: A Fast Algorithm for Counting Markov Equivalent DAGs and Designing Experiments
Ali AhmadiTeshnizi
Saber Salehkaleybar
Negar Kiyavash
CML
70
10
0
17 Jun 2020
Active Invariant Causal Prediction: Experiment Selection through
  Stability
Active Invariant Causal Prediction: Experiment Selection through Stability
Juan L. Gamella
C. Heinze-Deml
OOD
73
46
0
10 Jun 2020
Interventions and Counterfactuals in Tractable Probabilistic Models:
  Limitations of Contemporary Transformations
Interventions and Counterfactuals in Tractable Probabilistic Models: Limitations of Contemporary Transformations
I. Papantonis
Vaishak Belle
TPM
32
7
0
29 Jan 2020
Interventional Experiment Design for Causal Structure Learning
Interventional Experiment Design for Causal Structure Learning
AmirEmad Ghassami
Saber Salehkaleybar
Negar Kiyavash
CML
56
10
0
12 Oct 2019
Optimal experimental design via Bayesian optimization: active causal
  structure learning for Gaussian process networks
Optimal experimental design via Bayesian optimization: active causal structure learning for Gaussian process networks
Julius von Kügelgen
Paul Kishan Rubenstein
Bernhard Schölkopf
Adrian Weller
CML
86
20
0
09 Oct 2019
Learning Linear Non-Gaussian Causal Models in the Presence of Latent
  Variables
Learning Linear Non-Gaussian Causal Models in the Presence of Latent Variables
Saber Salehkaleybar
AmirEmad Ghassami
Negar Kiyavash
Kun Zhang
CML
48
44
0
11 Aug 2019
Experimental Design for Cost-Aware Learning of Causal Graphs
Experimental Design for Cost-Aware Learning of Causal Graphs
Erik M. Lindgren
Murat Kocaoglu
A. Dimakis
S. Vishwanath
CML
70
37
0
28 Oct 2018
Counting and Sampling from Markov Equivalent DAGs Using Clique Trees
Counting and Sampling from Markov Equivalent DAGs Using Clique Trees
AmirEmad Ghassami
Saber Salehkaleybar
Negar Kiyavash
Kun Zhang
CML
87
22
0
05 Feb 2018
Learning Causal Structures Using Regression Invariance
Learning Causal Structures Using Regression Invariance
AmirEmad Ghassami
Saber Salehkaleybar
Negar Kiyavash
Kun Zhang
OODCML
81
61
0
26 May 2017
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