Communities
Connect sessions
AI calendar
Organizations
Join Slack
Contact Sales
Search
Open menu
Home
Papers
2011.00641
Cited By
Active Structure Learning of Causal DAGs via Directed Clique Tree
Neural Information Processing Systems (NeurIPS), 2020
1 November 2020
C. Squires
Sara Magliacane
Kristjan Greenewald
Dmitriy A. Katz
Murat Kocaoglu
Karthikeyan Shanmugam
CML
Re-assign community
ArXiv (abs)
PDF
HTML
Github (7★)
Papers citing
"Active Structure Learning of Causal DAGs via Directed Clique Tree"
30 / 30 papers shown
Theoretical Guarantees for Causal Discovery on Large Random Graphs
Mathieu Chevalley
Arash Mehrjou
Patrick Schwab
CML
244
0
0
04 Nov 2025
Graph Distance Based on Cause-Effect Estimands with Latents
Zhufeng Li
Niki Kilbertus
CML
335
0
0
28 Oct 2025
Near-Optimal Experiment Design in Linear non-Gaussian Cyclic Models
Ehsan Sharifian
Saber Salehkaleybar
Negar Kiyavash
CML
207
1
0
25 Sep 2025
Design of Experiment for Discovering Directed Mixed Graph
Haijie Xu
Chen Zhang
CML
178
0
0
02 Sep 2025
Sample Complexity of Nonparametric Closeness Testing for Continuous Distributions and Its Application to Causal Discovery with Hidden Confounding
CLEaR (CLEaR), 2025
Fateme Jamshidi
S. Akbari
Negar Kiyavash
CML
310
1
0
10 Mar 2025
Sample Efficient Bayesian Learning of Causal Graphs from Interventions
Neural Information Processing Systems (NeurIPS), 2024
Zihan Zhou
Muhammad Qasim Elahi
Murat Kocaoglu
CML
352
4
0
26 Oct 2024
Interventional Causal Discovery in a Mixture of DAGs
Burak Varıcı
Dmitriy A. Katz-Rogozhnikov
Dennis L. Wei
P. Sattigeri
A. Tajer
CML
311
4
0
12 Jun 2024
Causal Discovery with Fewer Conditional Independence Tests
Kirankumar Shiragur
Jiaqi Zhang
Caroline Uhler
CML
281
11
0
03 Jun 2024
Adaptive Online Experimental Design for Causal Discovery
International Conference on Machine Learning (ICML), 2024
Muhammad Qasim Elahi
Lai Wei
Murat Kocaoglu
Mahsa Ghasemi
CML
379
2
0
19 May 2024
Causal Discovery under Off-Target Interventions
Davin Choo
Kirankumar Shiragur
Caroline Uhler
CML
227
4
1
13 Feb 2024
Meek Separators and Their Applications in Targeted Causal Discovery
Neural Information Processing Systems (NeurIPS), 2023
Kirankumar Shiragur
Jiaqi Zhang
Caroline Uhler
CML
251
3
0
30 Oct 2023
Adaptivity Complexity for Causal Graph Discovery
Conference on Uncertainty in Artificial Intelligence (UAI), 2023
Davin Choo
Kirankumar Shiragur
CML
219
4
0
09 Jun 2023
Active causal structure learning with advice
International Conference on Machine Learning (ICML), 2023
Davin Choo
Themis Gouleakis
Arnab Bhattacharyya
CML
260
8
0
31 May 2023
New metrics and search algorithms for weighted causal DAGs
International Conference on Machine Learning (ICML), 2023
Davin Choo
Kirankumar Shiragur
CML
274
1
0
08 May 2023
Practical Algorithms for Orientations of Partially Directed Graphical Models
CLEaR (CLEaR), 2023
Malte Luttermann
Marcel Wienöbst
Maciej Liskiewicz
CML
209
1
0
28 Feb 2023
Causal Bandits without Graph Learning
CLEaR (CLEaR), 2023
Mikhail Konobeev
Jalal Etesami
Negar Kiyavash
CML
290
10
0
26 Jan 2023
Subset verification and search algorithms for causal DAGs
International Conference on Artificial Intelligence and Statistics (AISTATS), 2023
Davin Choo
Kirankumar Shiragur
CML
473
14
0
09 Jan 2023
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
449
3
0
24 Nov 2022
Verification and search algorithms for causal DAGs
Neural Information Processing Systems (NeurIPS), 2022
Davin Choo
Kirankumar Shiragur
Arnab Bhattacharyya
CML
286
15
0
30 Jun 2022
Causal Structure Learning: a Combinatorial Perspective
Foundations of Computational Mathematics (FoCM), 2022
C. Squires
Caroline Uhler
CML
546
66
0
02 Jun 2022
A Unified Experiment Design Approach for Cyclic and Acyclic Causal Models
Journal of machine learning research (JMLR), 2022
Ehsan Mokhtarian
Saber Salehkaleybar
AmirEmad Ghassami
Negar Kiyavash
385
6
0
20 May 2022
Polynomial-Time Algorithms for Counting and Sampling Markov Equivalent DAGs with Applications
Journal of machine learning research (JMLR), 2022
Marcel Wienöbst
Max Bannach
Maciej Liskiewicz
375
15
0
05 May 2022
Interventions, Where and How? Experimental Design for Causal Models at Scale
Neural Information Processing Systems (NeurIPS), 2022
P. Tigas
Yashas Annadani
Andrew Jesson
Bernhard Schölkopf
Y. Gal
Stefan Bauer
CML
721
58
0
03 Mar 2022
Universal Lower Bound for Learning Causal DAGs with Atomic Interventions
Vibhor Porwal
P. Srivastava
Gaurav Sinha
CML
592
2
0
09 Nov 2021
Active-LATHE: An Active Learning Algorithm for Boosting the Error Exponent for Learning Homogeneous Ising Trees
Fengzhuo Zhang
Anshoo Tandon
Vincent Y. F. Tan
320
1
0
27 Oct 2021
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
420
51
0
06 Sep 2021
Efficient Online Estimation of Causal Effects by Deciding What to Observe
Shantanu Gupta
Zachary Chase Lipton
David Benjamin Childers
CML
452
19
0
20 Aug 2021
Matching a Desired Causal State via Shift Interventions
Jiaqi Zhang
C. Squires
Caroline Uhler
262
19
0
05 Jul 2021
Causal Bandits with Unknown Graph Structure
Neural Information Processing Systems (NeurIPS), 2021
Yangyi Lu
A. Meisami
Ambuj Tewari
CML
294
47
0
05 Jun 2021
Active Structure Learning of Bayesian Networks in an Observational Setting
Journal of machine learning research (JMLR), 2021
Noa Ben-David
Sivan Sabato
401
5
0
25 Mar 2021
1
Page 1 of 1
