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Jalal Etesami
Title
Cited by
Cited by
Year
Wasserstein adversarial imitation learning
H Xiao, M Herman, J Wagner, S Ziesche, J Etesami, TH Linh
arXiv preprint arXiv:1906.08113, 2019
782019
Learning network of multivariate hawkes processes: A time series approach
J Etesami, N Kiyavash, K Zhang, K Singhal
Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence …, 2016
772016
Online learning for multivariate Hawkes processes
Y Yang, J Etesami, N He, N Kiyavash
Advances in Neural Information Processing Systems 30, 2017
662017
Learning minimal latent directed information polytrees
J Etesami, N Kiyavash, T Coleman
Neural computation 28 (9), 1723-1768, 2016
41*2016
Directed information graphs: A generalization of linear dynamical graphs
J Etesami, N Kiyavash
2014 American control conference, 2563-2568, 2014
382014
LDPC code construction for wireless physical-layer key reconciliation
J Etesami, W Henkel
2012 1st IEEE International Conference on Communications in China (ICCC …, 2012
352012
Learning Hawkes processes under synchronization noise
W Trouleau, J Etesami, M Grossglauser, N Kiyavash, P Thiran
International Conference on Machine Learning, 6325-6334, 2019
252019
Measuring causal relationships in dynamical systems through recovery of functional dependencies
J Etesami, N Kiyavash
IEEE Transactions on Signal and Information Processing over Networks 3 (4 …, 2016
242016
Causal transfer for imitation learning and decision making under sensor-shift
J Etesami, P Geiger
Proceedings of the AAAI Conference on Artificial Intelligence 34 (06), 10118 …, 2020
182020
Sharp analysis of stochastic optimization under global Kurdyka-Lojasiewicz inequality
I Fatkhullin, J Etesami, N He, N Kiyavash
Advances in Neural Information Processing Systems 35, 15836-15848, 2022
152022
Econometric modeling of systemic risk: going beyond pairwise comparison and allowing for nonlinearity
J Etesami, A Habibnia, N Kiyavash
Systemic Risk Centre, The London School of Economics and Political Science, 2017
132017
Optimal attack strategies against predictors-learning from expert advice
A Truong, SR Etesami, J Etesami, N Kiyavash
IEEE Transactions on Information Forensics and Security 13 (1), 6-19, 2017
112017
Revisiting the General Identifiability Problem
Y Kivva, E Mokhtarian, J Etesami, N Kiyavash
38th Conference on Uncertainty in Artificial Intelligence (UAI), 2022
102022
Learning Bayesian Networks in the Presence of Structural Side Information
E Mokhtarian, S Akbari, F Jamshidi, J Etesami, N Kiyavash
AAAI - Association for the Advancement of Artificial Intelligence 2022, 2021
92021
Nonparametric hawkes processes: Online estimation and generalization bounds
Y Yang, J Etesami, N He, N Kiyavash
arXiv preprint arXiv:1801.08273, 2018
92018
Interventional dependency graphs: An approach for discovering influence structure
J Etesami, N Kiyavash
2016 IEEE International Symposium on Information Theory (ISIT), 1158-1162, 2016
9*2016
Causal Effect Identification with Context-specific Independence Relations of Control Variables
E Mokhtarian, F Jamshidi, J Etesami, N Kiyavash
International Conference on Artificial Intelligence and Statistics (AISTATS …, 2022
82022
A variational inference approach to learning multivariate wold processes
J Etesami, W Trouleau, N Kiyavash, M Grossglauser, P Thiran
International Conference on Artificial Intelligence and Statistics, 2044-2052, 2021
62021
Identifying nonlinear 1-step causal influences in presence of latent variables
S Salehkaleybar, J Etesami, N Kiyavash
2017 IEEE International Symposium on Information Theory (ISIT), 1341-1345, 2017
62017
Robust directed tree approximations for networks of stochastic processes
CJ Quinn, J Etesami, N Kiyavash, TP Coleman
2013 IEEE International Symposium on Information Theory, 2254-2258, 2013
52013
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Articles 1–20