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Model-Agnostic Human Preference Inversion in Diffusion Models
Efficient text-to-image generation remains a challenging task due to the high computational costs associated with the multi-step sampling in diffusion models.
Extract Dynamic Information To Improve Time Series Modeling: a Case Study with Scientific Workflow
In this work, we describe a number of techniques to extract dynamic information about the current state of a large scientific workflow, which could be generalized to other types of applications.
Improving Botnet Detection with Recurrent Neural Network and Transfer Learning
Botnet detection is a critical step in stopping the spread of botnets and preventing malicious activities.
Botnet Detection Using Recurrent Variational Autoencoder
Botnets are increasingly used by malicious actors, creating increasing threat to a large number of internet users.
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