{"id":21290200,"url":"https://github.com/ssydasheng/gpflow-slim","last_synced_at":"2025-09-11T00:45:13.833Z","repository":{"id":71453483,"uuid":"138372242","full_name":"ssydasheng/GPflow-Slim","owner":"ssydasheng","description":"customized GPflow with simple Tensorflow API","archived":false,"fork":false,"pushed_at":"2019-08-07T19:08:15.000Z","size":134,"stargazers_count":17,"open_issues_count":1,"forks_count":9,"subscribers_count":4,"default_branch":"master","last_synced_at":"2025-04-06T04:41:21.362Z","etag":null,"topics":["gaussian-processes","machine-learning"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"apache-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/ssydasheng.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":"2018-06-23T04:50:51.000Z","updated_at":"2022-10-21T11:15:49.000Z","dependencies_parsed_at":"2023-03-15T08:00:15.955Z","dependency_job_id":null,"html_url":"https://github.com/ssydasheng/GPflow-Slim","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/ssydasheng/GPflow-Slim","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ssydasheng%2FGPflow-Slim","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ssydasheng%2FGPflow-Slim/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ssydasheng%2FGPflow-Slim/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ssydasheng%2FGPflow-Slim/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/ssydasheng","download_url":"https://codeload.github.com/ssydasheng/GPflow-Slim/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ssydasheng%2FGPflow-Slim/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":264833280,"owners_count":23670617,"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":["gaussian-processes","machine-learning"],"created_at":"2024-11-21T12:45:47.064Z","updated_at":"2025-07-11T14:32:12.110Z","avatar_url":"https://github.com/ssydasheng.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# GPflow-Slim\nGPflow-Slim is a package for building Gaussian process models in python, using TensorFlow. It is adapted from \n[GPflow](https://github.com/GPflow/GPflow) and now contributed by [Shengyang Sun](https://github.com/ssydasheng/Neural-Kernel-Network/) \nand [Guodong Zhang](https://github.com/gd-zhang).\n\nCompared to GPflow, GPflow-Slim enables simpler Tensorflow-style programming. User can define variables arbitrarily\nanywhere in the program and apply standard Tensorflow optimizer to optimize the objective.\n\n## Install\nFor installing, please run\n```\npython setup.py develop\n```\n\n## Examples\nBelow we show a simple example to use GPflow-Slim and additionally defined variables.\n```\nX = tf.constant(np.random.normal(size=[20, 4]))\ny = tf.sin(X)\n\nvar_ = tf.get_variable('var', initializer=1.)\nkern = gpf.kernels.RBF(13, ARD=True) + tf.exp(var_)\nm = gpf.models.GPR(X, y, kern=kern)\n\nobjective = m.objective\noptimizer = tf.train.AdamOptimizer(1e-3)\ninfer = optimizer.minimize(objective)\nwith tf.Session() as sess:\n    sess.run(infer) \n```\nFor more examples, please refer [examples](./examples) as well as \n[Neural Kernel Network](https://github.com/ssydasheng/Neural-Kernel-Network).\n\n\n## Citation\nTo cite this work, please use\n```\n@article{sun2018differentiable,\n  title={Differentiable Compositional Kernel Learning for Gaussian Processes},\n  author={Sun, Shengyang and Zhang, Guodong and Wang, Chaoqi and Zeng, Wenyuan and Li, Jiaman and Grosse, Roger},\n  journal={arXiv preprint arXiv:1806.04326},\n  year={2018}\n}\n```\nas well as \n```\n@ARTICLE{GPflow2017,\n   author = {Matthews, Alexander G. de G. and {van der Wilk}, Mark and Nickson, Tom and\n\tFujii, Keisuke. and {Boukouvalas}, Alexis and {Le{\\'o}n-Villagr{\\'a}}, Pablo and\n\tGhahramani, Zoubin and Hensman, James},\n    title = \"{{GP}flow: A {G}aussian process library using {T}ensor{F}low}\",\n  journal = {Journal of Machine Learning Research},\n  year    = {2017},\n  month = {apr},\n  volume  = {18},\n  number  = {40},\n  pages   = {1-6},\n  url     = {http://jmlr.org/papers/v18/16-537.html}\n}\n```\n\n## Acknowledgement\nGPflow-Slim is adapted from [GPflow](https://github.com/GPflow/GPflow).\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fssydasheng%2Fgpflow-slim","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fssydasheng%2Fgpflow-slim","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fssydasheng%2Fgpflow-slim/lists"}