8 citations · 31 across the 22 of their papers we have counts for
5 papers · 1 filter
Transferring Information Across Interventions in Causal Bayesian Optimization
Mohammad Ali Javidian
Bayesian optimization is a popular way to optimize expensive systems, where every experiment, simulation, or intervention costs time or money. In its standard form, it treats the v…
Extending Multi-Source Bayesian Optimization With Causality Principles
Luuk Jacobs, Mohammad Ali Javidian
Multi-Source Bayesian Optimization (MSBO) serves as a variant of the traditional Bayesian Optimization (BO) framework applicable to situations involving optimization of an objectiv…
Multi-Objective Multi-Fidelity Bayesian Optimization with Causal Priors
Md Abir Hossen, Mohammad Ali Javidian, Vignesh Narayanan +2
Multi-fidelity Bayesian optimization (MFBO) accelerates the search for the global optimum of black-box functions by integrating inexpensive, low-fidelity approximations. The centra…
Causally-Aware Information Bottleneck for Domain Adaptation
Mohammad Ali Javidian
We tackle a common domain adaptation setting in causal systems. In this setting, the target variable is observed in the source domain but is entirely missing in the target domain.…
An Expectation-Maximization Algorithm for Domain Adaptation in Gaussian Causal Models
Mohammad Ali Javidian
We study the problem of imputing a designated target variable that is systematically missing in a shifted deployment domain, when a Gaussian causal DAG is available from a fully ob…