Wild-Time

Wild-Time is a benchmark of 5 datasets that reflect temporal distribution shifts arising in a variety of real-world applications, including patient prognosis and news classification. On these datasets, we systematically benchmark 13 prior approaches, including methods in domain generalization, continual learning, self-supervised learning, and ensemble learning.

Source: Wild-Time: A Benchmark of in-the-Wild Distribution Shift over Time

Image Source: https://arxiv.org/pdf/2211.14238v1.pdf