{"url":"/dataset/permuted-mnist","name":"Permuted MNIST","full_name":null,"description_markdown":"**Permuted MNIST** is an MNIST variant that consists of 70,000 images of handwritten digits from 0 to 9, where 60,000 images are used for training, and 10,000 images for test. The difference of this dataset from the original MNIST is that each of the ten tasks is the multi-class classification of a different random permutation of the input pixels.\r\n\r\nSource: [Lifelong Learning with Dynamically Expandable Networks](https://arxiv.org/abs/1708.01547)\r\nImage Source: [https://arxiv.org/pdf/1810.12488.pdf](https://arxiv.org/pdf/1810.12488.pdf)","description_withheld":null,"homepage":"","introduced_date":"2014-01-01","introduced_date_note":null,"introduced_by":{"paper":"/paper/an-empirical-investigation-of-catastrophic","title":"An Empirical Investigation of Catastrophic Forgetting in Gradient-Based Neural Networks","first_author":"Ian J. Goodfellow","url":null},"license":{"name":"Unknown","url":null},"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Continual Learning","url":"/task/continual-learning","datasets_with_task":"/datasets/task/continual-learning"},{"name":"Incremental Learning","url":"/task/incremental-learning","datasets_with_task":"/datasets/task/incremental-learning"},{"name":"Domain-IL Continual Learning","url":"/task/domain-il-continual-learning","datasets_with_task":"/datasets/task/domain-il-continual-learning"}],"languages":[],"variants":["Permuted MNIST"],"data_loaders":[],"num_papers_in_archive":121,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/continual-learning-on-permuted-mnist","task":"Continual Learning","dataset_variant":"Permuted MNIST","rows":3,"metrics":["Average Accuracy","MLP Hidden Layers-width","Pretrained/Transfer Learning","BWT"],"first_row_in_archive_order":{"model":"RMN","paper":"/paper/understanding-catastrophic-forgetting-and","metrics":{"Average Accuracy":"97.988","MLP Hidden Layers-width":"2-100","Pretrained/Transfer Learning":"No"},"code_links":[{"title":"prakhark2/relevance-mapping-networks","url":"https://gitlab.com/prakhark2/relevance-mapping-networks"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/code-cl-conceptor-based-gradient-projection","title":"CODE-CL: Conceptor-Based Gradient Projection for Deep Continual Learning","date":"2024-11-21","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/boosting-a-model-zoo-for-multi-task-and","title":"Model Zoo: A Growing \"Brain\" That Learns Continually","date":"2021-06-06","rows_on_this_dataset":1,"code_links":2,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":2,"samples_ran":0,"samples_unverified":2,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/understanding-catastrophic-forgetting-and","title":"Understanding Catastrophic Forgetting and Remembering in Continual Learning with Optimal Relevance Mapping","date":"2021-02-22","rows_on_this_dataset":1,"code_links":1,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":1,"samples_harvested":2,"samples_ran":0,"samples_unverified":2,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":1,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}