{"id":13698124,"url":"https://github.com/muammar/ml4chem","last_synced_at":"2025-06-17T09:04:18.390Z","repository":{"id":57442227,"uuid":"161847010","full_name":"muammar/ml4chem","owner":"muammar","description":"ML4Chem:  Machine Learning for Chemistry and Materials","archived":false,"fork":false,"pushed_at":"2024-12-09T17:11:58.000Z","size":2918,"stargazers_count":97,"open_issues_count":8,"forks_count":15,"subscribers_count":4,"default_branch":"master","last_synced_at":"2025-06-15T07:04:15.494Z","etag":null,"topics":["chemistry","deeplearning","kernel","kernel-methods","machine-learning","materials-science","physics"],"latest_commit_sha":null,"homepage":"https://ml4chem.dev","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/muammar.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":"2018-12-14T22:28:22.000Z","updated_at":"2025-06-02T20:16:17.000Z","dependencies_parsed_at":"2023-11-17T00:11:50.983Z","dependency_job_id":"4a2e5bf9-690d-4723-a99a-3036a3d71699","html_url":"https://github.com/muammar/ml4chem","commit_stats":{"total_commits":400,"total_committers":3,"mean_commits":"133.33333333333334","dds":"0.020000000000000018","last_synced_commit":"365487c23ea3386657e178e56ab31adfe8d5d073"},"previous_names":["muammar/mlchem"],"tags_count":9,"template":false,"template_full_name":null,"purl":"pkg:github/muammar/ml4chem","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/muammar%2Fml4chem","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/muammar%2Fml4chem/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/muammar%2Fml4chem/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/muammar%2Fml4chem/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/muammar","download_url":"https://codeload.github.com/muammar/ml4chem/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/muammar%2Fml4chem/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":259935602,"owners_count":22934386,"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":["chemistry","deeplearning","kernel","kernel-methods","machine-learning","materials-science","physics"],"created_at":"2024-08-02T19:00:40.313Z","updated_at":"2025-06-17T09:04:18.325Z","avatar_url":"https://github.com/muammar.png","language":"Python","funding_links":[],"categories":["Software","Python"],"sub_categories":[],"readme":"![alt text](https://raw.githubusercontent.com/muammar/ml4chem/master/docs/source/_static/ml4chem.png \"Logo\")\n\n--------------------------------------------------------------------------------\n\n## About\n[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/Django.svg)](https://github.com/muammar/mkchromecast/)\n[![Build Status](https://travis-ci.com/muammar/ml4chem.svg?branch=master)](https://travis-ci.com/muammar/ml4chem)\n[![License](https://img.shields.io/badge/license-BSD-green)](https://github.com/muammar/ml4chem/blob/master/LICENSE)\n[![Downloads](https://img.shields.io/github/downloads/muammar/ml4chem/total.svg?maxAge=2592000?style=flat-square)](https://github.com/muammar/ml4chem/releases)\n![PyPI - Downloads](https://img.shields.io/pypi/dm/ml4chem)\n[![GitHub release](https://img.shields.io/github/release/muammar/ml4chem.svg)](https://github.com/muammar/ml4chem/releases/latest)\n[![Documentation Status](https://readthedocs.org/projects/ml4chem/badge/?version=latest)](https://ml4chem.readthedocs.io/en/latest/?badge=latest)\n[![Slack channel](https://img.shields.io/badge/slack-ml4chem-yellow.svg?logo=slack)](https://ml4chem.slack.com/)\n\n\n\nML4Chem is a package to deploy machine learning for chemistry and materials\nscience. It is written in Python 3, and intends to offer modern and rich\nfeatures to perform machine learning (ML) workflows for chemical physics.\n\nA list of features and ML algorithms are shown below.\n\n- PyTorch backend.\n- Completely modular. You can use any part of this package in your project.\n- Free software \u003c3. No secrets! Pull requests and additions are more than\n  welcome!\n- Documentation (work in progress).\n- Explicit and idiomatic: `ml4chem.get_me_a_coffee()`.\n- Distributed training in a data parallel paradigm aka mini-batches.\n- Scalability and distributed computations are powered by Dask.\n- Real-time tools to track status of your computations.\n- Easy scaling up/down.\n- Easy access to intermediate quantities: `NeuralNetwork.get_activations(X, numpy=True)` or `VAE.get_latent_space(X)`.\n- [Messagepack serialization](https://msgpack.org/index.html).\n\n## Notes \n\nThis package is under heavy development and might break at some points until\nit gets stabilized. It is in its infancy, so if you find there is an error,\nyou might want to report it so that it can be improved. We also welcome pull\nrequests if you find any part of ML4Chem should be improved. That would be\nvery nice.\n\n## Citing\n\nIf you find this software useful, please use this bibtex to cite it:\n\n```\n@article{El_Khatib2020,\nauthor = \"Muammar El Khatib and Wibe de Jong\",\ntitle = \"{ML4Chem: A Machine Learning Package for Chemistry and Materials Science}\",\nyear = \"2020\",\nmonth = \"3\",\nurl = \"https://chemrxiv.org/articles/ML4Chem_A_Machine_Learning_Package_for_Chemistry_and_Materials_Science/11952516\",\ndoi = \"10.26434/chemrxiv.11952516.v1\"\n}\n```\n\n## Documentation\n\nTo get started, read the documentation at\n[https://ml4chem.dev](https://ml4chem.dev). It is arranged in a way that you\ncan go through the theory as well as some code snippets to understand how to\nuse this software. Additionally, you can dive through the [module\nindex](https://ml4chem.dev/genindex.html) to get more information about\ndifferent classes and functions of ML4Chem. If you think the documentation\nhas to be improved do not hesistate to state so in the bug reports and help\nout if you feel like it.\n\n\n## Visualizations\n\n![](https://raw.githubusercontent.com/muammar/ml4chem/master/docs/source/_static/dask_dashboard.png)\n\n## Copyright\n\nLicense: BSD 3-clause \"New\" or \"Revised\" License.\n\n```\nML4Chem: Machine Learning for Chemistry and Materials (ML4Chem) Copyright (c)\n2019, The Regents of the University of California, through Lawrence Berkeley\nNational Laboratory (subject to receipt of any required approvals from the U.S.\nDept. of Energy).  All rights reserved.\n\nIf you have questions about your rights to use or distribute this software,\nplease contact Berkeley Lab's Intellectual Property Office at\nIPO@lbl.gov.\n\nNOTICE.  This Software was developed under funding from the U.S. Department\nof Energy and the U.S. Government consequently retains certain rights.  As\nsuch, the U.S. Government has been granted for itself and others acting on\nits behalf a paid-up, nonexclusive, irrevocable, worldwide license in the\nSoftware to reproduce, distribute copies to the public, prepare derivative\nworks, and perform publicly and display publicly, and to permit other to do\nso.\n```","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmuammar%2Fml4chem","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmuammar%2Fml4chem","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmuammar%2Fml4chem/lists"}