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Directed Information Graphs
IEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2012
9 April 2012
Christopher J. Quinn
Negar Kiyavash
Todd P. Coleman
CML
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Papers citing
"Directed Information Graphs"
39 / 39 papers shown
Modeling Systemic Risk: A Time-Varying Nonparametric Causal Inference Framework
Jalal Etesami
Ali Habibnia
Negar Kiyavash
155
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27 Dec 2023
Information Theoretically Optimal Sample Complexity of Learning Dynamical Directed Acyclic Graphs
International Conference on Artificial Intelligence and Statistics (AISTATS), 2023
M. S. Veedu
Sidhant Misra
M. Salapaka
292
1
0
31 Aug 2023
Approximate Causal Effect Identification under Weak Confounding
International Conference on Machine Learning (ICML), 2023
Ziwei Jiang
Lai Wei
Murat Kocaoglu
CML
195
3
0
22 Jun 2023
Temporally Causal Discovery Tests for Discrete Time Series and Neural Spike Trains
IEEE Transactions on Signal Processing (IEEE TSP), 2023
A. Theocharous
G. Gregoriou
P. Sapountzis
Ioannis Kontoyiannis
CML
300
6
0
23 May 2023
CEBoosting: Online Sparse Identification of Dynamical Systems with Regime Switching by Causation Entropy Boosting
Chaos (Chaos), 2023
Chuanqi Chen
Nan Chen
Jin-Long Wu
406
15
0
16 Apr 2023
Data-Driven Optimization of Directed Information over Discrete Alphabets
IEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2023
Dor Tsur
Ziv Aharoni
Ziv Goldfeld
Haim Permuter
236
14
0
02 Jan 2023
A Causality-Based Learning Approach for Discovering the Underlying Dynamics of Complex Systems from Partial Observations with Stochastic Parameterization
Social Science Research Network (SSRN), 2022
Nan Chen
Yinling Zhang
CML
317
19
0
19 Aug 2022
Causal Imitative Model for Autonomous Driving
Mohammad Reza Samsami
Mohammadhossein Bahari
Saber Salehkaleybar
Alexandre Alahi
CML
203
14
0
07 Dec 2021
Causal Discovery in Linear Structural Causal Models with Deterministic Relations
CLEaR (CLEaR), 2021
Yuqin Yang
M. Nafea
AmirEmad Ghassami
Negar Kiyavash
CML
325
4
0
30 Oct 2021
Efficient and passive learning of networked dynamical systems driven by non-white exogenous inputs
Harish Doddi
Sidhant Misra
Saurav Talukdar
M. Salapaka
393
7
0
02 Oct 2021
Causal Graph Discovery from Self and Mutually Exciting Time Series
IEEE Journal on Selected Areas in Information Theory (JSAIT), 2021
S. Wei
Yao Xie
C. Josef
Rishikesan Kamaleswaran
CML
461
2
0
04 Jun 2021
On the Consistency of Maximum Likelihood Estimators for Causal Network Identification
IEEE Conference on Decision and Control (CDC), 2020
Xiaotian Xie
Dimitrios Katselis
Carolyn L. Beck
R. Srikant
CML
208
4
0
17 Oct 2020
Propagation Graph Estimation from Individual's Time Series of Observed States
Tatsuya Hayashi
Atsuyoshi Nakamura
AI4TS
151
1
0
11 May 2020
Variable-lag Granger Causality and Transfer Entropy for Time Series Analysis
ACM Transactions on Knowledge Discovery from Data (TKDD), 2020
Chainarong Amornbunchornvej
Elena Zheleva
T. Berger-Wolf
CML
422
56
0
01 Feb 2020
Variable-lag Granger Causality for Time Series Analysis
International Conference on Data Science and Advanced Analytics (DSAA), 2019
Chainarong Amornbunchornvej
Elena Zheleva
T. Berger-Wolf
CML
AI4TS
345
22
0
18 Dec 2019
Graph Learning Under Partial Observability
Vincenzo Matta
A. Santos
Ali H. Sayed
422
0
0
18 Dec 2019
Learning Hawkes Processes from a Handful of Events
Neural Information Processing Systems (NeurIPS), 2019
Farnood Salehi
W. Trouleau
Matthias Grossglauser
Patrick Thiran
BDL
CML
394
42
0
01 Nov 2019
Adversarial Orthogonal Regression: Two non-Linear Regressions for Causal Inference
Neural Networks (NN), 2019
M. Heydari
Saber Salehkaleybar
Kun Zhang
CML
166
6
0
10 Sep 2019
Time-Varying Interaction Estimation Using Ensemble Methods
Data Science Workshop (DS), 2019
Brandon Oselio
Amir Sadeghian
Silvio Savarese
Alfred Hero
104
1
0
25 Jun 2019
Topology Inference over Networks with Nonlinear Coupling
A. Santos
Vincenzo Matta
Ali H. Sayed
291
0
0
21 Jun 2019
Graph Learning over Partially Observed Diffusion Networks: Role of Degree Concentration
Vincenzo Matta
A. Santos
Ali H. Sayed
449
2
0
05 Apr 2019
Physics Informed Topology Learning in Networks of Linear Dynamical Systems
Saurav Talukdar
Sidhant Misra
Harish Doddi
D. Materassi
Michael Chertkov
M. Salapaka
AI4CE
160
24
0
27 Sep 2018
Structure Learning from Time Series with False Discovery Control
Bernat Guillen Pegueroles
B. Vinzamuri
Karthikeyan Shanmugam
S. Hedden
Jonathan D. Moyer
Kush R. Varshney
CML
AI4TS
113
2
0
24 May 2018
Local Tomography of Large Networks under the Low-Observability Regime
A. Santos
Vincenzo Matta
Ali H. Sayed
334
28
0
23 May 2018
Detecting Nonlinear Causality in Multivariate Time Series with Sparse Additive Models
Yingxiang Yang
Adams Wei Yu
Zhaoran Wang
T. Zhao
204
3
0
11 Mar 2018
Graph2Seq: Scalable Learning Dynamics for Graphs
S. Venkatakrishnan
Mohammad Alizadeh
Pramod Viswanath
GNN
283
12
0
14 Feb 2018
Potential Conditional Mutual Information: Estimators, Properties and Applications
Arman Rahimzamani
Sreeram Kannan
272
11
0
13 Oct 2017
Budgeted Experiment Design for Causal Structure Learning
AmirEmad Ghassami
Saber Salehkaleybar
Negar Kiyavash
Elias Bareinboim
CML
415
71
0
11 Sep 2017
CausalGAN: Learning Causal Implicit Generative Models with Adversarial Training
Murat Kocaoglu
Christopher Snyder
A. Dimakis
S. Vishwanath
GAN
OOD
516
296
0
06 Sep 2017
Consistent Tomography under Partial Observations over Adaptive Networks
Vincenzo Matta
Ali H. Sayed
316
35
0
20 Jul 2017
Learning Causal Structures Using Regression Invariance
AmirEmad Ghassami
Saber Salehkaleybar
Negar Kiyavash
Kun Zhang
OOD
CML
265
71
0
26 May 2017
Cost-Optimal Learning of Causal Graphs
Murat Kocaoglu
A. Dimakis
S. Vishwanath
CML
281
75
0
08 Mar 2017
Entropic Causality and Greedy Minimum Entropy Coupling
International Symposium on Information Theory (ISIT), 2017
Murat Kocaoglu
A. Dimakis
S. Vishwanath
B. Hassibi
149
20
0
28 Jan 2017
Mixing Times and Structural Inference for Bernoulli Autoregressive Processes
IEEE Transactions on Network Science and Engineering (IEEE Trans. Netw. Sci. Eng.), 2016
Dimitrios Katselis
Carolyn L. Beck
R. Srikant
223
16
0
19 Dec 2016
Entropic Causal Inference
Murat Kocaoglu
A. Dimakis
S. Vishwanath
B. Hassibi
CML
268
81
0
12 Nov 2016
Causal Compression
Aleksander Wieczorek
Volker Roth
CML
99
4
0
01 Nov 2016
Learning Network of Multivariate Hawkes Processes: A Time Series Approach
Jalal Etesami
Negar Kiyavash
Kun Zhang
K. Singhal
CML
AI4TS
182
65
0
14 Mar 2016
Tractable Fully Bayesian Inference via Convex Optimization and Optimal Transport Theory
Sanggyun Kim
Diego A. Mesa
Rui Ma
Todd P. Coleman
151
4
0
29 Sep 2015
Learning Loosely Connected Markov Random Fields
R. Wu
R. Srikant
J. Ni
394
22
0
25 Apr 2012
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