115 citations · 136 across the 7 of their papers we have counts for
7 papers
A State-Space Approach to Nonstationary Discriminant Analysis
Shuilian Xie, Mahdi Imani, Edward R. Dougherty +1
Classical discriminant analysis assumes identically distributed training data, yet in many applications observations are collected over time and the class-conditional distributions…
A Bayesian Optimization Framework for Finding Local Optima in Expensive Multi-Modal Functions
Yongsheng Mei, Tian Lan, Mahdi Imani +1
Bayesian optimization (BO) is a popular global optimization scheme for sample-efficient optimization in domains with expensive function evaluations. The existing BO techniques are…
Inference of Regulatory Networks Through Temporally Sparse Data
Mohammad Alali, Mahdi Imani
A major goal in genomics is to properly capture the complex dynamical behaviors of gene regulatory networks (GRNs). This includes inferring the complex interactions between genes,…
Scalable optimal Bayesian classification of single-cell trajectories under regulatory model uncertainty
Ehsan Hajiramezanali, Mahdi Imani, Ulisses Braga-Neto +2
Single-cell gene expression measurements offer opportunities in deriving mechanistic understanding of complex diseases, including cancer. However, due to the complex regulatory mac…
Sequential Experimental Design for Optimal Structural Intervention in Gene Regulatory Networks Based on the Mean Objective Cost of Uncertainty
Mahdi Imani, Roozbeh Dehghannasiri, Ulisses M. Braga-Neto +1
Scientists are attempting to use models of ever increasing complexity, especially in medicine, where gene-based diseases such as cancer require better modeling of cell regulation.…
Control of Gene Regulatory Networks with Noisy Measurements and Uncertain Inputs
Mahdi Imani, Ulisses Braga-Neto
This paper is concerned with the problem of stochastic control of gene regulatory networks (GRNs) observed indirectly through noisy measurements and with uncertainty in the interve…
Particle Filters for Partially-Observed Boolean Dynamical Systems
Mahdi Imani, Ulisses Braga-Neto
Partially-observed Boolean dynamical systems (POBDS) are a general class of nonlinear models with application in estimation and control of Boolean processes based on noisy and inco…