Python-SSM状态空间模型的贝叶斯学习与推理

上传者: 39841365 | 上传时间: 2021-09-15 15:09:34 | 文件大小: 4.17MB | 文件类型: ZIP
该软件包具有快速灵活的代码,可用于在各种状态空间模型中进行模拟,学习和执行推理。

文件下载

资源详情

[{"title":"( 50 个子文件 4.17MB ) Python-SSM状态空间模型的贝叶斯学习与推理","children":[{"title":"ssm-master","children":[{"title":".travis.yml <span style='color:#111;'> 776B </span>","children":null,"spread":false},{"title":"tests","children":[{"title":"test_hmm_gradients.py <span style='color:#111;'> 2.61KB </span>","children":null,"spread":false},{"title":"test_basics.py <span style='color:#111;'> 7.40KB </span>","children":null,"spread":false},{"title":"test_stats.py <span style='color:#111;'> 8.53KB </span>","children":null,"spread":false},{"title":"test_lds.py <span style='color:#111;'> 13.91KB </span>","children":null,"spread":false}],"spread":true},{"title":"LICENSE <span style='color:#111;'> 1.06KB </span>","children":null,"spread":false},{"title":"ssm","children":[{"title":"preprocessing.py <span style='color:#111;'> 5.27KB </span>","children":null,"spread":false},{"title":"messages.pyx <span style='color:#111;'> 7.18KB </span>","children":null,"spread":false},{"title":"primitives.py <span style='color:#111;'> 17.61KB </span>","children":null,"spread":false},{"title":"lds.py <span style='color:#111;'> 45.56KB </span>","children":null,"spread":false},{"title":"transitions.py <span style='color:#111;'> 22.66KB </span>","children":null,"spread":false},{"title":"stats.py <span style='color:#111;'> 21.77KB </span>","children":null,"spread":false},{"title":"emissions.py <span style='color:#111;'> 31.38KB </span>","children":null,"spread":false},{"title":"optimizers.py <span style='color:#111;'> 4.96KB </span>","children":null,"spread":false},{"title":"variational.py <span style='color:#111;'> 12.12KB </span>","children":null,"spread":false},{"title":"util.py <span style='color:#111;'> 15.04KB </span>","children":null,"spread":false},{"title":"__init__.py <span style='color:#111;'> 64B </span>","children":null,"spread":false},{"title":"init_state_distns.py <span style='color:#111;'> 1.27KB </span>","children":null,"spread":false},{"title":"observations.py <span style='color:#111;'> 64.38KB </span>","children":null,"spread":false},{"title":"model_selection.py <span style='color:#111;'> 2.96KB </span>","children":null,"spread":false},{"title":"hierarchical.py <span style='color:#111;'> 5.12KB </span>","children":null,"spread":false},{"title":"hmm.py <span style='color:#111;'> 33.25KB </span>","children":null,"spread":false},{"title":"cstats.pyx <span style='color:#111;'> 8.86KB </span>","children":null,"spread":false}],"spread":false},{"title":"doc","children":[{"title":"constrained_ar_sampling","children":[{"title":"Constrained ARHMM Sampling.ipynb <span style='color:#111;'> 1.18MB </span>","children":null,"spread":false},{"title":"Constrained ARHMM Sampling.py <span style='color:#111;'> 11.03KB </span>","children":null,"spread":false}],"spread":true},{"title":"students_t","children":[{"title":"EM for the Students t distribution.ipynb <span style='color:#111;'> 118.40KB </span>","children":null,"spread":false}],"spread":true}],"spread":true},{"title":"examples","children":[{"title":"rslds.py <span style='color:#111;'> 5.83KB </span>","children":null,"spread":false},{"title":"lds.py <span style='color:#111;'> 3.56KB </span>","children":null,"spread":false},{"title":"slds.py <span style='color:#111;'> 4.55KB </span>","children":null,"spread":false},{"title":"hsmm.py <span style='color:#111;'> 3.70KB </span>","children":null,"spread":false},{"title":"hmm.py <span style='color:#111;'> 3.52KB </span>","children":null,"spread":false}],"spread":true},{"title":"setup.py <span style='color:#111;'> 1.33KB </span>","children":null,"spread":false},{"title":".gitignore <span style='color:#111;'> 1.27KB </span>","children":null,"spread":false},{"title":"CODE_OF_CONDUCT.md <span style='color:#111;'> 3.28KB </span>","children":null,"spread":false},{"title":"README.md <span style='color:#111;'> 1.93KB </span>","children":null,"spread":false},{"title":"notebooks","children":[{"title":"5 Poisson SLDS.ipynb <span style='color:#111;'> 365.63KB </span>","children":null,"spread":false},{"title":"6 Poisson fLDS.py <span style='color:#111;'> 3.64KB </span>","children":null,"spread":false},{"title":"4 Recurrent SLDS.py <span style='color:#111;'> 6.30KB </span>","children":null,"spread":false},{"title":"3 Switching Linear Dynamical System.py <span style='color:#111;'> 5.18KB </span>","children":null,"spread":false},{"title":"1 Simple HMM Demo.ipynb <span style='color:#111;'> 302.84KB </span>","children":null,"spread":false},{"title":"2 Input Driven HMM.ipynb <span style='color:#111;'> 68.58KB </span>","children":null,"spread":false},{"title":"2 Input Driven HMM.py <span style='color:#111;'> 4.20KB </span>","children":null,"spread":false},{"title":"1b Simple Linear Dynamical System.ipynb <span style='color:#111;'> 1.04MB </span>","children":null,"spread":false},{"title":"1 Simple HMM Demo.py <span style='color:#111;'> 3.67KB </span>","children":null,"spread":false},{"title":"4 Recurrent SLDS.ipynb <span style='color:#111;'> 598.24KB </span>","children":null,"spread":false},{"title":"5 Poisson SLDS.py <span style='color:#111;'> 3.61KB </span>","children":null,"spread":false},{"title":"6 Poisson fLDS.ipynb <span style='color:#111;'> 928.56KB </span>","children":null,"spread":false},{"title":"7 Variatonal Laplace EM for SLDS Tutorial.ipynb <span style='color:#111;'> 585.89KB </span>","children":null,"spread":false},{"title":"3 Switching Linear Dynamical System.ipynb <span style='color:#111;'> 382.15KB </span>","children":null,"spread":false},{"title":"1b Simple Linear Dynamical System.py <span style='color:#111;'> 9.62KB </span>","children":null,"spread":false}],"spread":false}],"spread":false}],"spread":true}]

评论信息

  • itnerd :
    https://github.com/slinderman/ssm
    2020-03-25

免责申明

【只为小站】的资源来自网友分享,仅供学习研究,请务必在下载后24小时内给予删除,不得用于其他任何用途,否则后果自负。基于互联网的特殊性,【只为小站】 无法对用户传输的作品、信息、内容的权属或合法性、合规性、真实性、科学性、完整权、有效性等进行实质审查;无论 【只为小站】 经营者是否已进行审查,用户均应自行承担因其传输的作品、信息、内容而可能或已经产生的侵权或权属纠纷等法律责任。
本站所有资源不代表本站的观点或立场,基于网友分享,根据中国法律《信息网络传播权保护条例》第二十二条之规定,若资源存在侵权或相关问题请联系本站客服人员,zhiweidada#qq.com,请把#换成@,本站将给予最大的支持与配合,做到及时反馈和处理。关于更多版权及免责申明参见 版权及免责申明