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of 157
pro vyhledávání: '"Imani, Mahdi"'
Bayesian games model interactive decision-making where players have incomplete information -- e.g., regarding payoffs and private data on players' strategies and preferences -- and must actively reason and update their belief models (with regard to s
Externí odkaz:
http://arxiv.org/abs/2405.14122
With the advancements of artificial intelligence (AI), we're seeing more scenarios that require AI to work closely with other agents, whose goals and strategies might not be known beforehand. However, existing approaches for training collaborative ag
Externí odkaz:
http://arxiv.org/abs/2403.15341
Bayesian optimization (BO) has established itself as a leading strategy for efficiently optimizing expensive-to-evaluate functions. Existing BO methods mostly rely on Gaussian process (GP) surrogate models and are not applicable to (doubly-stochastic
Externí odkaz:
http://arxiv.org/abs/2401.14544
Bayesian optimization (BO) is a popular global optimization scheme for sample-efficient optimization in domains with expensive function evaluations. The existing BO techniques are capable of finding a single global optimum solution. However, finding
Externí odkaz:
http://arxiv.org/abs/2210.06635
Autor:
Alali, Mohammad, Imani, Mahdi
Publikováno v:
Front Control Eng. 2022;3
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, which can be used for a wide range of genomics analyses, including dia
Externí odkaz:
http://arxiv.org/abs/2207.12124
Autor:
Pouyanasab, Babak1, Imani, Mahdi2 mimani@shirazu.ac.ir, Taghavi, Mohammareza3, Goodarzi, Mohammad Ali3
Publikováno v:
Journal of Research in Psychopathology. May2024, Vol. 5 Issue 16, p36-43. 8p.
Autor:
Hajiramezanali, Ehsan, Imani, Mahdi, Braga-Neto, Ulisses, Qian, Xiaoning, Dougherty, Edward R
Publikováno v:
BMC Genomics 2019
Single-cell gene expression measurements offer opportunities in deriving mechanistic understanding of complex diseases, including cancer. However, due to the complex regulatory machinery of the cell, gene regulatory network (GRN) model inference base
Externí odkaz:
http://arxiv.org/abs/1902.03188
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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. Complex models suffer from uncertainty and experiments are needed to r
Externí odkaz:
http://arxiv.org/abs/1805.12253