Explaining Survival Predictions with Shapley Values

Machine learning models are increasingly used to predict time-to-event outcomes — for example, how long a patient might survive after treatment or when a machine is likely to fail. Unlike standard predictions, these models produce survival curves, which change over time. Existing explanation tools like Shapley values can tell us which features matter, but they … Read more

Synthetic tabular data generation with large language models (taken)

In this project, we embark on an in-depth exploration of the possibilities and capabilities associated with the generation of synthetic tabular data. Our approach involves harnessing the power of pre-trained large language models, which have demonstrated remarkable prowess in understanding and generating natural language text. Through this endeavor, we aim to unlock the potential of … Read more