{"id":18401703,"url":"https://github.com/borealisai/monotonicity-mixup","last_synced_at":"2026-05-16T18:08:21.263Z","repository":{"id":67756481,"uuid":"422409090","full_name":"BorealisAI/monotonicity-mixup","owner":"BorealisAI","description":"Code of \"Not Too Close and Not Too Far: Enforcing Monotonicity Requires Penalizing The Right Points\"","archived":false,"fork":false,"pushed_at":"2021-12-16T23:09:30.000Z","size":43,"stargazers_count":1,"open_issues_count":0,"forks_count":1,"subscribers_count":4,"default_branch":"main","last_synced_at":"2025-09-21T00:26:46.500Z","etag":null,"topics":["monotonicity","neurips-2021","pytorch","xai4debugging"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"other","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/BorealisAI.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,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2021-10-29T01:46:57.000Z","updated_at":"2023-09-08T18:28:01.000Z","dependencies_parsed_at":"2023-02-25T00:16:39.425Z","dependency_job_id":null,"html_url":"https://github.com/BorealisAI/monotonicity-mixup","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/BorealisAI/monotonicity-mixup","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/BorealisAI%2Fmonotonicity-mixup","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/BorealisAI%2Fmonotonicity-mixup/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/BorealisAI%2Fmonotonicity-mixup/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/BorealisAI%2Fmonotonicity-mixup/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/BorealisAI","download_url":"https://codeload.github.com/BorealisAI/monotonicity-mixup/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/BorealisAI%2Fmonotonicity-mixup/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":33113509,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-16T04:41:52.686Z","status":"ssl_error","status_checked_at":"2026-05-16T04:41:52.009Z","response_time":115,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.5:443 state=error: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"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":["monotonicity","neurips-2021","pytorch","xai4debugging"],"created_at":"2024-11-06T02:39:41.477Z","updated_at":"2026-05-16T18:08:21.244Z","avatar_url":"https://github.com/BorealisAI.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Enforcing monotonicity in neural networks\n\nThis repo contains the code for the paper: \n#### [Not Too Close and Not Too Far: Enforcing Monotonicity Requires Penalizing The Right Points](https://openreview.net/forum?id=xdFqKVlDHnY) \nby Joao Monteiro\u003csup\u003e1\u003c/sup\u003e, Mohamed Osama Ahmed\u003csup\u003e2\u003c/sup\u003e, Hossein Hajimirsadeghi\u003csup\u003e2\u003c/sup\u003e, and Greg Mori\u003csup\u003e2\u003c/sup\u003e\n\n1. Institut National de la Recherche Scientifique\n2. Borealis AI\n\n## Running experiments\n\nWe provide scripts to easily launch experiments once requirememnts are installed.\n\nExamples:\n\n```\n./submit_all_reg.sh blogData cmn_MLP\n```\n\nOr, for experiments with synthetic data:\n\n```\n./synth_train_all_reg.sh cmn_MLP\n```\n\n### Data preparation\n\nData needs to be prepared in advance and placed under ./exp/data/\n\nWe provide scripts to prepare data and to generate the data required for synthetic experiments under ./data_utils/\n\nRaw data for a subset of the datasets we consider can be found at:\n\n- COMPAS: https://github.com/gnobitab/CertifiedMonotonicNetwork/blob/main/compas/compas_scores_two_years.csv\n- BlogFeedback: https://archive.ics.uci.edu/ml/datasets/BlogFeedback#.\n\n## Citation:\n\n```\n@inproceedings{\nmonteiro2021not,\ntitle={Not Too Close and Not Too Far:  Enforcing Monotonicity Requires Penalizing The Right Points},\nauthor={Joao Monteiro and Mohamed Osama Ahmed and Hossein Hajimirsadeghi and Greg Mori},\nbooktitle={eXplainable AI approaches for debugging and diagnosis.},\nyear={2021},\nurl={https://openreview.net/forum?id=xdFqKVlDHnY}\n}\n```","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fborealisai%2Fmonotonicity-mixup","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fborealisai%2Fmonotonicity-mixup","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fborealisai%2Fmonotonicity-mixup/lists"}