{"id":24991671,"url":"https://github.com/ht0710/qlstm","last_synced_at":"2025-10-16T02:02:55.471Z","repository":{"id":272825925,"uuid":"917323407","full_name":"HT0710/QLSTM","owner":"HT0710","description":"Official repository of paper \"Modified Quantum Long-Short Term Memory with Variational Quantum Circuits for PV Power Forecasting\"","archived":false,"fork":false,"pushed_at":"2025-05-07T02:43:37.000Z","size":32132,"stargazers_count":0,"open_issues_count":0,"forks_count":1,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-08-04T13:51:41.481Z","etag":null,"topics":["deep-learning","forecasting","long-short-term-memory","machie-learning","photovoltaic-power","quantum","research-project"],"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/HT0710.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,"zenodo":null}},"created_at":"2025-01-15T19:11:09.000Z","updated_at":"2025-05-12T05:17:48.000Z","dependencies_parsed_at":"2025-01-16T21:26:02.960Z","dependency_job_id":"eef3c442-6d61-4718-8c66-dbb90660f9cd","html_url":"https://github.com/HT0710/QLSTM","commit_stats":null,"previous_names":["ht0710/qlstm"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/HT0710/QLSTM","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/HT0710%2FQLSTM","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/HT0710%2FQLSTM/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/HT0710%2FQLSTM/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/HT0710%2FQLSTM/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/HT0710","download_url":"https://codeload.github.com/HT0710/QLSTM/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/HT0710%2FQLSTM/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":279139969,"owners_count":26112492,"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":"2025-10-16T02:00:06.019Z","response_time":53,"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":["deep-learning","forecasting","long-short-term-memory","machie-learning","photovoltaic-power","quantum","research-project"],"created_at":"2025-02-04T13:51:12.140Z","updated_at":"2025-10-16T02:02:55.425Z","avatar_url":"https://github.com/HT0710.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# \u003cp align=\"center\"\u003eModified Quantum Long-Short Term Memory with Variational Quantum Circuits for PV Power Forecasting\u003c/p\u003e\n![CLSTM drawio](https://github.com/user-attachments/assets/8ef76e0c-c6de-4a5b-9c9d-4111b9c0b2e9)\n\n## Table of Contents\n- [Modified Quantum Long-Short Term Memory with Variational Quantum Circuits for PV Power Forecasting](#modified-quantum-long-short-term-memory-with-variational-quantum-circuits-for-pv-power-forecasting)\n  - [Introduction](#introduction)\n  - [Requirements](#requirements)\n  - [Configuration](#configuration)\n  - [Train](#train)\n  - [Logging](#logging)\n  - [Demo App](#demo-app)\n  - [License](#license)\n  - [Contact](#contact)\n\n## Introduction\nThis repository presents a hybrid AI model that integrates Quantum Machine Learning (QML) and Deep Learning to deliver fast, cost-efficient, and highly accurate photovoltaic (PV) power forecasting. By embedding Variational Quantum Circuits (VQCs) within a modified Long Short-Term Memory (LSTM) framework, we propose a model that not only improves prediction accuracy but also significantly reduces computational resources and time compared to classical ML and deep learning counterparts.\n\n## Requirements\nProject is tested with **Python \u003e= 3.10**\n\n```bash\npip install -r requirements.txt\n```\n\n## Configuration\nMost of the configuration for this project can be changed in `/qlstm/configs/`:  \n- `train.yaml` for training\n- `callbacks.yaml` for logging and training behavior\n\n**To change training model**:\n1. Use or create new model class in `qlstm/models`\n2. Import and define your model at line 42 in `qlstm/train.py`.\n3. Change model config in `qlstm/configs/train.yaml`\n\n**For datasets with difference structure**:\n1. Create a custom data module at `qlstm/modules/data.py` inherited from `CustomDataModule` class.  \n2. Import and define your custom data module at line 39 in `qlstm/train.py`.\n3. Change data config in `qlstm/configs/train.yaml`\n\n## Train\nModify the configurations in `qlstm/configs/train.yaml` then run:\n```bash\npython qlstm/train.py\n```\n  \nWith CLI:\n```bash\npython qlstm/train.py -h\n```\nExample:\n```bash\npython qlstm/train.py trainer.accelerator=cpu optimizer=0.001\n```\n\n## Logging\nNote: Use full path\n```bash\ntensorboard --logdir /home/USER/.../QLSTM/lightning_logs\n```\n\n## Demo App\nBuilt with **Gradio**.\n\nLaunch local:\n```bash\npython app/app.py\n```\n\nLaunch public:\n```bash\npython app/app.py --share\n# or\npython app/app.py -s\n```\n\n## License\nThis project is licensed under the MIT License. See [LICENSE](https://github.com/HT0710/QLSTM/blob/main/LICENSE) for more details.\n\n## Contact\nOpen an issue: [New issue](https://github.com/HT0710/QLSTM/issues/new)\n\nMail: pthung7102002@gmail.com\n\n---\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fht0710%2Fqlstm","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fht0710%2Fqlstm","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fht0710%2Fqlstm/lists"}