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1206.3250
Cited By
Almost Optimal Intervention Sets for Causal Discovery
Conference on Uncertainty in Artificial Intelligence (UAI), 2008
13 June 2012
F. Eberhardt
CML
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Papers citing
"Almost Optimal Intervention Sets for Causal Discovery"
30 / 30 papers shown
Theoretical Guarantees for Causal Discovery on Large Random Graphs
Mathieu Chevalley
Arash Mehrjou
Patrick Schwab
CML
206
0
0
04 Nov 2025
On the identifiability of causal graphs with multiple environments
Francesco Montagna
CML
292
0
0
15 Oct 2025
Event-Triggered Nonlinear Model Predictive Control for Cooperative Cable-Suspended Payload Transportation with Multi-Quadrotors
Tohid Kargar Tasooji
Sakineh Khodadadi
Guangjun Liu
203
0
0
26 Mar 2025
When Selection Meets Intervention: Additional Complexities in Causal Discovery
International Conference on Learning Representations (ICLR), 2025
Haoyue Dai
Ignavier Ng
Jianle Sun
Zeyu Tang
Gongxu Luo
Xinshuai Dong
Peter Spirtes
Kun Zhang
CML
296
5
0
10 Mar 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
260
0
0
10 Mar 2025
Interventional Causal Structure Discovery over Graphical Models with Convergence and Optimality Guarantees
IEEE Transactions on Network Science and Engineering (TNSE), 2024
Qiu Chengbo
Yang Kai
CML
242
2
0
09 Aug 2024
Everything that can be learned about a causal structure with latent variables by observational and interventional probing schemes
Marina Maciel Ansanelli
Elie Wolfe
Robert W. Spekkens
CML
124
1
0
01 Jul 2024
Learning Flexible Time-windowed Granger Causality Integrating Heterogeneous Interventional Time Series Data
Knowledge Discovery and Data Mining (KDD), 2024
Ziyi Zhang
Shaogang Ren
Xiaoning Qian
Nick Duffield
AI4TS
CML
204
5
0
14 Jun 2024
Learning Causal Representations from General Environments: Identifiability and Intrinsic Ambiguity
Jikai Jin
Vasilis Syrgkanis
CML
352
10
0
21 Nov 2023
Do we become wiser with time? On causal equivalence with tiered background knowledge
Conference on Uncertainty in Artificial Intelligence (UAI), 2023
Christine W. Bang
Vanessa Didelez
201
6
0
02 Jun 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
397
3
0
24 Nov 2022
Unifying Causal Inference and Reinforcement Learning using Higher-Order Category Theory
Sridhar Mahadevan
159
4
0
13 Sep 2022
On The Universality of Diagrams for Causal Inference and The Causal Reproducing Property
Sridhar Mahadevan
200
5
0
06 Jul 2022
Active Bayesian Causal Inference
Neural Information Processing Systems (NeurIPS), 2022
Christian Toth
Lars Lorch
Christian Knoll
Andreas Krause
Franz Pernkopf
Robert Peharz
Julius von Kügelgen
264
40
0
04 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
298
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
262
15
0
05 May 2022
Universal Lower Bound for Learning Causal DAGs with Atomic Interventions
Vibhor Porwal
P. Srivastava
Gaurav Sinha
CML
484
2
0
09 Nov 2021
Causal Homotopy
Sridhar Mahadevan
CML
162
6
0
20 Sep 2021
Asymptotic Causal Inference
Sridhar Mahadevan
CML
141
2
0
20 Sep 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
309
50
0
06 Sep 2021
Efficient Neural Causal Discovery without Acyclicity Constraints
International Conference on Learning Representations (ICLR), 2021
Phillip Lippe
Taco S. Cohen
E. Gavves
CML
360
85
0
22 Jul 2021
Causal Structure Learning: a Bayesian approach based on random graphs
Mauricio Gonzalez-Soto
Ivan Feliciano-Avelino
L. Sucar
Hugo Jair Escalante
CML
117
0
0
13 Oct 2020
Differentiable Causal Discovery from Interventional Data
P. Brouillard
Sébastien Lachapelle
Alexandre Lacoste
Damien Scieur
Alexandre Drouin
CML
395
230
0
03 Jul 2020
LazyIter: A Fast Algorithm for Counting Markov Equivalent DAGs and Designing Experiments
Ali AhmadiTeshnizi
Saber Salehkaleybar
Negar Kiyavash
CML
197
12
0
17 Jun 2020
Active Invariant Causal Prediction: Experiment Selection through Stability
Neural Information Processing Systems (NeurIPS), 2020
Juan L. Gamella
C. Heinze-Deml
OOD
385
50
0
10 Jun 2020
Interventional Experiment Design for Causal Structure Learning
AmirEmad Ghassami
Saber Salehkaleybar
Negar Kiyavash
CML
165
11
0
12 Oct 2019
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
206
21
0
09 Oct 2019
Characterizing and Learning Equivalence Classes of Causal DAGs under Interventions
Karren D. Yang
Abigail Katoff
Caroline Uhler
CML
322
115
0
17 Feb 2018
Identifying Best Interventions through Online Importance Sampling
International Conference on Machine Learning (ICML), 2017
Rajat Sen
Karthikeyan Shanmugam
A. Dimakis
Sanjay Shakkottai
282
77
0
10 Jan 2017
Characterization and Greedy Learning of Interventional Markov Equivalence Classes of Directed Acyclic Graphs
Alain Hauser
Peter Buhlmann
CML
350
458
0
14 Apr 2011
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