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Ehsan Mokhtarian
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2020 – today
- 2024
- [c9]Amir Mohammad Abouei, Ehsan Mokhtarian
, Negar Kiyavash:
s-ID: Causal Effect Identification in a Sub-population. AAAI 2024: 20302-20310 - [c8]Ishan Agrawal, Zhijing Jin, Ehsan Mokhtarian, Siyuan Guo, Yuen Chen, Mrinmaya Sachan, Bernhard Schölkopf:
CausalCite: A Causal Formulation of Paper Citations. ACL (Findings) 2024: 8395-8410 - [i12]Ehsan Mokhtarian
Recursive Causal Discovery. CoRR abs/2403.09300 (2024) - [i11]Amir Mohammad Abouei, Ehsan Mokhtarian, Negar Kiyavash, Matthias Grossglauser:
Causal Effect Identification in a Sub-Population with Latent Variables. CoRR abs/2405.14547 (2024) - 2023
- [j1]Ehsan Mokhtarian
A Unified Experiment Design Approach for Cyclic and Acyclic Causal Models. J. Mach. Learn. Res. 24: 354:1-354:31 (2023) - [c7]Ehsan Mokhtarian
Novel Ordering-Based Approaches for Causal Structure Learning in the Presence of Unobserved Variables. AAAI 2023: 12260-12268 - [c6]Sina Akbari, Fateme Jamshidi, Ehsan Mokhtarian, Matthew J. Vowels, Jalal Etesami, Negar Kiyavash:
Causal Effect Identification in Uncertain Causal Networks. NeurIPS 2023 - [i10]Amir Mohammad Abouei, Ehsan Mokhtarian, Negar Kiyavash:
s-ID: Causal Effect Identification in a Sub-Population. CoRR abs/2309.02281 (2023) - [i9]Ishan Kumar, Zhijing Jin, Ehsan Mokhtarian
CausalCite: A Causal Formulation of Paper Citations. CoRR abs/2311.02790 (2023) - 2022
- [c5]Ehsan Mokhtarian
Learning Bayesian Networks in the Presence of Structural Side Information. AAAI 2022: 7814-7822 - [c4]Ehsan Mokhtarian
Causal Effect Identification with Context-specific Independence Relations of Control Variables. AISTATS 2022: 11237-11246 - [c3]Yaroslav Kivva, Ehsan Mokhtarian
Revisiting the general identifiability problem. UAI 2022: 1022-1030 - [i8]Ehsan Mokhtarian, Saber Salehkaleybar
A Unified Experiment Design Approach for Cyclic and Acyclic Causal Models. CoRR abs/2205.10083 (2022) - [i7]Yaroslav Kivva, Ehsan Mokhtarian, Jalal Etesami, Negar Kiyavash:
Revisiting the General Identifiability Problem. CoRR abs/2206.01081 (2022) - [i6]Sina Akbari, Fateme Jamshidi, Ehsan Mokhtarian, Matthew J. Vowels, Jalal Etesami, Negar Kiyavash:
Causal Discovery in Probabilistic Networks with an Identifiable Causal Effect. CoRR abs/2208.04627 (2022) - [i5]Ehsan Mokhtarian, Mohammadsadegh Khorasani, Jalal Etesami, Negar Kiyavash:
Novel Ordering-based Approaches for Causal Structure Learning in the Presence of Unobserved Variables. CoRR abs/2208.06935 (2022) - 2021
- [c2]Ehsan Mokhtarian
A Recursive Markov Boundary-Based Approach to Causal Structure Learning. CD@KDD 2021: 26-54 - [c1]Sina Akbari, Ehsan Mokhtarian, AmirEmad Ghassami, Negar Kiyavash:
Recursive Causal Structure Learning in the Presence of Latent Variables and Selection Bias. NeurIPS 2021: 10119-10130 - [i4]Sina Akbari, Ehsan Mokhtarian, AmirEmad Ghassami, Negar Kiyavash:
Recursive Causal Structure Learning in the Presence of Latent Variables and Selection Bias. CoRR abs/2110.12036 (2021) - [i3]Ehsan Mokhtarian, Fateme Jamshidi, Jalal Etesami, Negar Kiyavash:
Causal Effect Identification with Context-specific Independence Relations of Control Variables. CoRR abs/2110.12064 (2021) - [i2]Ehsan Mokhtarian, Sina Akbari, Fateme Jamshidi, Jalal Etesami, Negar Kiyavash:
Learning Bayesian Networks in the Presence of Structural Side Information. CoRR abs/2112.10884 (2021) - 2020
- [i1]Ehsan Mokhtarian, Sina Akbari, AmirEmad Ghassami, Negar Kiyavash:
A Recursive Markov Blanket-Based Approach to Causal Structure Learning. CoRR abs/2010.04992 (2020)
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