Haoyu Li

Haoyu Li

Mathematics of Computation @ UCLA

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Data Attribution

Computational Machine Learning

less than 1 minute read

Published:

The field of machine learning has witnessed a surge in research on generative models, as these models possess the ability to generate novel data similar to the training data. In this study, our primary objective is to explore various types of generative models, with a thorough analysis of their respective limitations and potential applications. Additionally, we will investigate several influence methods and explore their efficacy in addressing the issue of memorization in generative models.

Diffusion Models

Computational Machine Learning

less than 1 minute read

Published:

The field of machine learning has witnessed a surge in research on generative models, as these models possess the ability to generate novel data similar to the training data. In this study, our primary objective is to explore various types of generative models, with a thorough analysis of their respective limitations and potential applications. Additionally, we will investigate several influence methods and explore their efficacy in addressing the issue of memorization in generative models.

Influence

Computational Machine Learning

less than 1 minute read

Published:

The field of machine learning has witnessed a surge in research on generative models, as these models possess the ability to generate novel data similar to the training data. In this study, our primary objective is to explore various types of generative models, with a thorough analysis of their respective limitations and potential applications. Additionally, we will investigate several influence methods and explore their efficacy in addressing the issue of memorization in generative models.

Interpretability

Computational Machine Learning

less than 1 minute read

Published:

The field of machine learning has witnessed a surge in research on generative models, as these models possess the ability to generate novel data similar to the training data. In this study, our primary objective is to explore various types of generative models, with a thorough analysis of their respective limitations and potential applications. Additionally, we will investigate several influence methods and explore their efficacy in addressing the issue of memorization in generative models.