Mohammad Ali Javidian

CoRR, February, 2026

Multi-Objective Multi-Fidelity Bayesian Optimization with Causal Priors.

[BibT_eX]

[DOI]

Md. Abir Hossen

Vignesh Narayanan

Jason M. O'Kane

CoRR, February, 2026

Causally-Aware Information Bottleneck for Domain Adaptation.

[BibT_eX]

[DOI]

CoRR, January, 2026

An Expectation-Maximization Algorithm for Domain Adaptation in Gaussian Causal Models.

[BibT_eX]

[DOI]

CoRR, January, 2026

2025

EM-Based Transfer Learning for Gaussian Causal Models Under Covariate and Target Shift.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Data Mining, 2025

2022

Unicorn: reasoning about configurable system performance through the lens of causality.

[BibT_eX]

[DOI]

Md Shahriar Iqbal

Rahul Krishna

Baishakhi Ray

Proceedings of the EuroSys '22: Seventeenth European Conference on Computer Systems, Rennes, France, April 5, 2022

2021

A decomposition-based algorithm for learning the structure of multivariate regression chain graphs.

[BibT_eX]

[DOI]

Int. J. Approx. Reason., 2021

Learning Circular Hidden Quantum Markov Models: A Tensor Network Approach.

[BibT_eX]

[DOI]

Vaneet Aggarwal

Zubin Jacob

CoRR, 2021

Quantum Causal Inference in the Presence of Hidden Common Causes: an Entropic Approach.

[BibT_eX]

[DOI]

Vaneet Aggarwal

Zubin Jacob

CoRR, 2021

Scalable Causal Transfer Learning.

[BibT_eX]

[DOI]

Om Pandey

CoRR, 2021

Quantum Entropic Causal Inference.

[BibT_eX]

[DOI]

Vaneet Aggarwal

Fanglin Bao

Zubin Jacob

CoRR, 2021

An Order-Independent Algorithm for Learning Chain Graphs.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fourth International Florida Artificial Intelligence Research Society Conference, 2021

Accelerating Recursive Partition-Based Causal Structure Learning.

[BibT_eX]

[DOI]

Md. Musfiqur Rahman

Ayman Rasheed

Md. Mosaddek Khan

Md. Mamun-Or-Rashid

Proceedings of the AAMAS '21: 20th International Conference on Autonomous Agents and Multiagent Systems, 2021

2020

AMP Chain Graphs: Minimal Separators and Structure Learning Algorithms.

[BibT_eX]

[DOI]

J. Artif. Intell. Res., 2020

CADET: A Systematic Method For Debugging Misconfigurations using Counterfactual Reasoning.

[BibT_eX]

[DOI]

Rahul Krishna

Md Shahriar Iqbal

Baishakhi Ray

CoRR, 2020

Learning LWF Chain Graphs: an Order Independent Algorithm.

[BibT_eX]

[DOI]

CoRR, 2020

On a hypergraph probabilistic graphical model.

[BibT_eX]

[DOI]

Zhiyu Wang

Linyuan Lu

Ann. Math. Artif. Intell., 2020

Learning LWF Chain Graphs: A Markov Blanket Discovery Approach.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

2019

Transfer Learning for Performance Modeling of Configurable Systems: A Causal Analysis.

[BibT_eX]

[DOI]

CoRR, 2019

Order-Independent Structure Learning of Multivariate Regression Chain Graphs.

[BibT_eX]

[DOI]

Proceedings of the Scalable Uncertainty Management - 13th International Conference, 2019

Avoiding Social Disappointment in Elections.

[BibT_eX]

[DOI]

Rasoul Ramezanian

Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, 2019

2018

Comment on: Decomposition of structural learning about directed acyclic graphs [1].

[BibT_eX]

[DOI]

CoRR, 2018

A Proof of the Front-Door Adjustment Formula.

[BibT_eX]

[DOI]

CoRR, 2018

Structural Learning of Multivariate Regression Chain Graphs via Decomposition.

[BibT_eX]

[DOI]

CoRR, 2018

The evolution of multivariate regression chain graphs.

[BibT_eX]

[DOI]

CoRR, 2018

How can social planners prevent disappointment in an election?

[BibT_eX]

[DOI]

Rasoul Ramezanian

CoRR, 2018

Finding Minimal Separators in LWF Chain Graphs.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Probabilistic Graphical Models, 2018

2013

Disappointment in Social Choice Protocols

[BibT_eX]

[DOI]