{"url":"/dataset/experimental-results-for-a-unified","name":"Experimental Results for \"A Unified Perspective on Natural Gradient Variational Inference with Gaussian Mixture Models\"","full_name":null,"description_markdown":"This package contains the raw data / logs (fetched from WandB) for the experiments of the following publication:\r\n\r\nO. Arenz, P. Dahlinger, Z. Ye, M. Volpp, and G. Neumann. A unified perspective on natural gradient variational inference with gaussian mixture models. Transactions on Machine Learning Research, 2023. URL: https://openreview.net/forum?id=tLBjsX4tjs.","description_withheld":null,"homepage":"https://doi.org/10.5281/zenodo.8158833","introduced_date":"2023-07-18","introduced_date_note":null,"introduced_by":{"paper":"/paper/a-unified-perspective-on-natural-gradient","title":"A Unified Perspective on Natural Gradient Variational Inference with Gaussian Mixture Models","first_author":"Oleg Arenz","url":null},"license":{"name":"Creative Commons Attribution 4.0 International","url":null},"modalities":[],"tasks":[],"languages":[],"variants":["Experimental Results for \"A Unified Perspective on Natural Gradient Variational Inference with Gaussian Mixture Models\""],"data_loaders":[],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"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."}