most citedAnalyzing Quality, Bias, and Performance in Text-to-Image Generative Models

2 citations · 2 across the 2 of their papers we have counts for

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2 papers

cs.AI2024★ 2 cited

Analyzing Quality, Bias, and Performance in Text-to-Image Generative Models

Nila Masrourisaadat, Nazanin Sedaghatkish, Fatemeh Sarshartehrani +1

Advances in generative models have led to significant interest in image synthesis, demonstrating the ability to generate high-quality images for a diverse range of text prompts. De…

math.OC2021

Convergence Rates of Decentralized Gradient Methods over Cluster Networks

Amit Dutta, Nila Masrourisaadat, Thinh T. Doan

We present an analysis for the performance of decentralized consensus-based gradient (DCG) methods for solving optimization problems over a cluster network of nodes. This type of n…