{"url":"/dataset/binarized-mnist","name":"Binarized MNIST","full_name":null,"description_markdown":"A binarized version of MNIST.\r\n\r\nSource: [Binarized MNIST](http://www.dmi.usherb.ca/~larocheh/mlpython/_modules/datasets/binarized_mnist.html)","description_withheld":null,"homepage":"http://www.dmi.usherb.ca/~larocheh/mlpython/_modules/datasets/binarized_mnist.html","introduced_date":null,"introduced_date_note":null,"introduced_by":null,"license":null,"modalities":[],"tasks":[{"name":"Image Generation","url":"/task/image-generation","datasets_with_task":"/datasets/task/image-generation"}],"languages":[],"variants":["Binarized MNIST"],"data_loaders":[{"repo":"https://github.com/tensorflow/datasets","url":"https://www.tensorflow.org/datasets/catalog/binarized_mnist","frameworks":["tf","jax"]}],"num_papers_in_archive":10,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/image-generation-on-binarized-mnist","task":"Image Generation","dataset_variant":"Binarized MNIST","rows":10,"metrics":["nats","bits/dimension"],"first_row_in_archive_order":{"model":"CR-NVAE","paper":"/paper/consistency-regularization-for-variational","metrics":{"nats":"76.93"},"code_links":[{"title":"sinhasam/crvae","url":"https://github.com/sinhasam/crvae"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/bayesian-flow-networks","title":"Bayesian Flow Networks","date":"2023-08-14","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":14,"samples_ran":11,"samples_unverified":3,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/efficient-vdvae-less-is-more","title":"Efficient-VDVAE: Less is more","date":"2022-03-25","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/consistency-regularization-for-variational","title":"Consistency Regularization for Variational Auto-Encoders","date":"2021-05-31","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":3,"samples_ran":0,"samples_unverified":3,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/locally-masked-convolution-for-autoregressive","title":"Locally Masked Convolution for Autoregressive Models","date":"2020-06-22","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/pixel-recurrent-neural-networks","title":"Pixel Recurrent Neural Networks","date":"2016-01-25","rows_on_this_dataset":2,"code_links":20,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":29,"samples_ran":19,"samples_unverified":10,"pointer_only_for_licence":18,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/made-masked-autoencoder-for-distribution","title":"MADE: Masked Autoencoder for Distribution Estimation","date":"2015-02-12","rows_on_this_dataset":1,"code_links":18,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":9,"samples_ran":5,"samples_unverified":4,"pointer_only_for_licence":1,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/iterative-neural-autoregressive-distribution","title":"Iterative Neural Autoregressive Distribution Estimator NADE-k","date":"2014-12-01","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/iterative-neural-autoregressive-distribution-1","title":"Iterative Neural Autoregressive Distribution Estimator (NADE-k)","date":"2014-06-05","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/a-deep-and-tractable-density-estimator","title":"A Deep and Tractable Density Estimator","date":"2013-10-07","rows_on_this_dataset":1,"code_links":1,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":4,"samples_harvested":55,"samples_ran":35,"samples_unverified":20,"pointer_only_for_licence":19,"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."}