{"id":19146472,"url":"https://github.com/kahsolt/wheelqnet","last_synced_at":"2026-06-18T22:32:08.054Z","repository":{"id":215594928,"uuid":"732605864","full_name":"Kahsolt/WheelQNet","owner":"Kahsolt","description":"Official implementaion of WheelQNet, yet another toyish quantum binary classifier implemented in pyVQNet","archived":false,"fork":false,"pushed_at":"2024-01-05T09:51:11.000Z","size":1805,"stargazers_count":2,"open_issues_count":0,"forks_count":1,"subscribers_count":2,"default_branch":"master","last_synced_at":"2025-02-22T19:49:41.465Z","etag":null,"topics":["contest-solution","quantum-classifier","vqnet"],"latest_commit_sha":null,"homepage":"","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/Kahsolt.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}},"created_at":"2023-12-17T08:39:39.000Z","updated_at":"2024-05-20T10:24:34.000Z","dependencies_parsed_at":"2024-01-05T10:59:54.615Z","dependency_job_id":"50bdf6e7-4cbb-4d4d-9d74-f21637db9c5d","html_url":"https://github.com/Kahsolt/WheelQNet","commit_stats":null,"previous_names":["kahsolt/wheelqnet"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/Kahsolt/WheelQNet","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Kahsolt%2FWheelQNet","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Kahsolt%2FWheelQNet/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Kahsolt%2FWheelQNet/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Kahsolt%2FWheelQNet/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Kahsolt","download_url":"https://codeload.github.com/Kahsolt/WheelQNet/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Kahsolt%2FWheelQNet/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":34510283,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-26T15:22:16.424Z","status":"online","status_checked_at":"2026-06-18T02:00:06.871Z","response_time":128,"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":["contest-solution","quantum-classifier","vqnet"],"created_at":"2024-11-09T07:44:14.145Z","updated_at":"2026-06-18T22:32:08.037Z","avatar_url":"https://github.com/Kahsolt.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# WheelQNet: Quantum Binary Classification via Rotation Averaging\n\n    Official implementaion of WheelQNet, yet another toyish quantum binary classifier implemented in pyVQNet\n\n----\n\nThis repo contains code for the contest: 第一届量子信息技术与应用创新大赛 -- 本源量子VQNet量子机器学习大赛赛道  \nContest page: [https://contest.originqc.com.cn/contest/32/contest:introduction](https://contest.originqc.com.cn/contest/32/contest:introduction)  \nTeam Name: 做好坠机准备  \nFinal Score: **84.6** (the 1st prize 😀)  \n\n![wheelq](img/wheelq.png)\n\n| Model | Param cnt. | Train acc. | Test acc. |\n| :-: | :-: | :-: | :-: |\n| HEA    | 32 | 78.608% | 82.178% |\n| CCQC   | 52 | 79.494% | 81.188% |\n| CCQC-q | 52 | 80.253% | 78.218% |\n| WheelQ | 32 | 77.342% | 79.208% |\n| kNN-q  |  - | 81.392% | 87.129% |\n\n⚠ only `CCQC` has 1 classical parameter, and `kNN-q` is non-parametrical, the other models are all pure quantum parametricalized :)\nℹ the proposed `WheelQNet` looks 花里胡哨 though, it just works!! 🎉\nℹ the proposed `kNN-q` looks good, but it may be our fortune 😂\n\n\n### Quickstart\n\n⚪ install\n\n- `conda create -n vq python==3.8`\n- `conda activare vq`\n- `pip install -r requirements.txt`\n\n⚪ run\n\n- `python -m src.preprocess -f`, make feature data\n- `python -m src.eval -L log\\\u003cmodel\u003e`, get testset predictions\n  - `python -m src.eval` for the default model (`knnq`)\n- `run_vqnet.cmd`, train on your own to reproduce the submission\n\n⚪ development\n\n- `pip install -r requirements_dev.txt`\n- `python preprocess.py -f`\n- `python run_sklearn.py` for classical comparations\n- `python run_vqnet.py -M \u003cmodel\u003e` to train\n  - see exmaples in `run_vqnet*.cmd`\n- `python run_vqnet.py -L \u003clogdir\u003e` to eval\n\n\n#### refenrence\n\n⚪ Q framework \u0026 method\n\n- QPanda: [https://qpanda-tutorial.readthedocs.io/zh/latest/](https://qpanda-tutorial.readthedocs.io/zh/latest/)\n- PyQPanda: [https://pyqpanda-toturial.readthedocs.io/zh/latest/index.html](https://pyqpanda-toturial.readthedocs.io/zh/latest/index.html)\n- VQNet: [https://vqnet20-tutorial.readthedocs.io/en/latest/](https://vqnet20-tutorial.readthedocs.io/en/latest/)\n- HEA (Hardware Efficient Ansatz): [https://arxiv.org/abs/1704.05018](https://arxiv.org/abs/1704.05018)\n- CQCC (Circuit-Centric Quantum Classifiers): [https://arxiv.org/abs/1804.00633](https://arxiv.org/abs/1804.00633)\n- YouroQNet: [https://github.com/Kahsolt/YouroQNet](https://github.com/Kahsolt/YouroQNet)\n\n⚪ problem \u0026 data\n\n- kaggle page: [https://www.kaggle.com/competitions/titanic/overview](https://www.kaggle.com/competitions/titanic/overview)\n- solution guide: [https://towardsdatascience.com/a-beginners-guide-to-kaggle-s-titanic-problem-3193cb56f6ca](https://towardsdatascience.com/a-beginners-guide-to-kaggle-s-titanic-problem-3193cb56f6ca)\n\n\n#### Citation\n\nIf you find this work useful, please give a star ⭐ and cite~ 😃\n\n```\n@misc{kahsolt2023,\n  author = {Kahsolt},\n  title  = {WheelQNet: Quantum Binary Classification via Rotation Averaging},\n  howpublished = {\\url{https://github.com/Kahsolt/WheelQNet}}\n  month  = {December},\n  year   = {2023}\n}\n```\n\n----\nby Armit\n2023/10/27\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkahsolt%2Fwheelqnet","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fkahsolt%2Fwheelqnet","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkahsolt%2Fwheelqnet/lists"}