{"id":30897627,"url":"https://github.com/pasteurlabs/unreasonable_effective_der","last_synced_at":"2025-10-19T02:14:56.596Z","repository":{"id":46375674,"uuid":"494005512","full_name":"pasteurlabs/unreasonable_effective_der","owner":"pasteurlabs","description":"Supplementary material to reproduce \"The Unreasonable Effectiveness of Deep Evidential Regression\"","archived":false,"fork":false,"pushed_at":"2022-11-28T18:38:00.000Z","size":29876,"stargazers_count":19,"open_issues_count":0,"forks_count":4,"subscribers_count":2,"default_branch":"main","last_synced_at":"2024-01-25T12:10:02.473Z","etag":null,"topics":["confidence","deep-learning","evidence","neural-network","pytorch","uncertainty"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/pasteurlabs.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2022-05-19T09:29:48.000Z","updated_at":"2023-11-08T10:38:56.000Z","dependencies_parsed_at":"2022-07-19T21:59:19.813Z","dependency_job_id":null,"html_url":"https://github.com/pasteurlabs/unreasonable_effective_der","commit_stats":null,"previous_names":[],"tags_count":3,"template":false,"template_full_name":null,"purl":"pkg:github/pasteurlabs/unreasonable_effective_der","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pasteurlabs%2Funreasonable_effective_der","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pasteurlabs%2Funreasonable_effective_der/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pasteurlabs%2Funreasonable_effective_der/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pasteurlabs%2Funreasonable_effective_der/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/pasteurlabs","download_url":"https://codeload.github.com/pasteurlabs/unreasonable_effective_der/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pasteurlabs%2Funreasonable_effective_der/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":274231108,"owners_count":25245685,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","status":"online","status_checked_at":"2025-09-08T02:00:09.813Z","response_time":121,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["confidence","deep-learning","evidence","neural-network","pytorch","uncertainty"],"created_at":"2025-09-09T00:14:01.167Z","updated_at":"2025-10-19T02:14:56.514Z","avatar_url":"https://github.com/pasteurlabs.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"[![arXiv](https://img.shields.io/badge/arXiv-2205.10060-b31b1b.svg)](https://arxiv.org/abs/2205.10060)\n[![Python 3.8](https://img.shields.io/badge/python-3.8-blue.svg)](https://www.python.org/downloads/release/python-380/)\n\n# The Unreasonable Effectiveness of Deep Evidential Regression\n\nThis repository contains the paper and the supplementary material to reproduce _The Unreasonable Effectiveness of Deep Evidential Regression_:\n - [unreasonable_effective_der.pdf](unreasonable_effective_der.pdf): The paper and the Appendix.\n - [understanding_sota.ipynb](understanding_sota.ipynb): Introduction and high-level overview.\n - [x3_indepth.ipynb](x3_indepth.ipynb): Analysis of one-dimensional cubic regression data set.\n - [binpulse.ipynb](binpulse.ipynb): Analysis of binary pulse experiment.\n - [depth_estimation.ipynb](depth_estimation.ipynb): Notebook that was used to generate the figures of the Monocular Depth Estimation experiment.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpasteurlabs%2Funreasonable_effective_der","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fpasteurlabs%2Funreasonable_effective_der","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpasteurlabs%2Funreasonable_effective_der/lists"}