{"id":17218199,"url":"https://github.com/hbaniecki/compress-then-explain","last_synced_at":"2025-04-11T18:32:51.837Z","repository":{"id":246310733,"uuid":"820410431","full_name":"hbaniecki/compress-then-explain","owner":"hbaniecki","description":"Efficient and accurate explanation estimation with distribution compression (ICLR 2025 Spotlight)","archived":false,"fork":false,"pushed_at":"2025-02-11T17:52:09.000Z","size":1308,"stargazers_count":6,"open_issues_count":0,"forks_count":1,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-03-25T14:25:26.072Z","etag":null,"topics":["dalex","explainable-ai","feature-attribution","goodpoints","interpretable-machine-learning","kernel-thinning","pdp","sage","shap"],"latest_commit_sha":null,"homepage":"https://openreview.net/forum?id=LiUfN9h0Lx","language":"Python","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/hbaniecki.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":"2024-06-26T12:15:15.000Z","updated_at":"2025-02-16T16:55:37.000Z","dependencies_parsed_at":"2024-06-27T05:24:59.572Z","dependency_job_id":"642678f6-58bc-46b2-aa76-cfe2c7814917","html_url":"https://github.com/hbaniecki/compress-then-explain","commit_stats":null,"previous_names":["hbaniecki/compress-then-explain"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/hbaniecki%2Fcompress-then-explain","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/hbaniecki%2Fcompress-then-explain/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/hbaniecki%2Fcompress-then-explain/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/hbaniecki%2Fcompress-then-explain/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/hbaniecki","download_url":"https://codeload.github.com/hbaniecki/compress-then-explain/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248458856,"owners_count":21107166,"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","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":["dalex","explainable-ai","feature-attribution","goodpoints","interpretable-machine-learning","kernel-thinning","pdp","sage","shap"],"created_at":"2024-10-15T03:45:45.998Z","updated_at":"2025-04-11T18:32:51.811Z","avatar_url":"https://github.com/hbaniecki.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Compress Then Explain\n\nThis repository is a supplement to [the following paper](https://openreview.net/forum?id=LiUfN9h0Lx):\n\n\u003e Hubert Baniecki, Giuseppe Casalicchio, Bernd Bischl, Przemyslaw Biecek. *Efficient and Accurate Explanation Estimation with Distribution Compression*. **ICLR 2025 (Spotlight)**\n\n![](images/fig1.png)\n\n### Start: examples\n\nIn `examples`, we provide 4 Jupyter notebooks with simple code examples on how to use CTE to improve the estimation of SHAP, SAGE, Expected Gradients, and Feature Effects.\n\n### Details: experiments\n\nIn `experiments`, we provide code to reproduce the results reported in Section 4 of the paper.\n\n### Citation\n\n```bibtex\n@inproceedings{baniecki2025efficient,\n    title     = {Efficient and Accurate Explanation Estimation with Distribution Compression},\n    author    = {Hubert Baniecki and \n                 Giuseppe Casalicchio and \n                 Bernd Bischl and \n                 Przemyslaw Biecek},\n    booktitle = {International Conference on Learning Representations},\n    year      = {2025},\n    url       = {https://openreview.net/forum?id=LiUfN9h0Lx}\n}\n```\n\n### Acknowledgements\n\nThis work was financially supported by the Polish National Science Centre grant number 2021/43/O/ST6/00347. Hubert Baniecki gratefully acknowledges scholarship funding from the Polish National Agency for Academic Exchange under the Preludium Bis NAWA 3 programme.\n\n\u003cimg src=\"images/logo.png\" width=\"300px\"\u003e","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fhbaniecki%2Fcompress-then-explain","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fhbaniecki%2Fcompress-then-explain","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fhbaniecki%2Fcompress-then-explain/lists"}