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- 来自专栏Debian中国
Debian的版本号及distributions
debian archive里真正的distribution目录用的是code name，比如sarge、etch，其他名字的distribution目录如stable/testing/unstable、debian 3.1等都是指向code name目录的符号连结。用code name的好处是可以一致地指定一个distribution，而不管该distribution release的状态，譬如当前处于testing的etch distribtuion在release后仍然可以用etch来引用它。
1.2K30发布于 2018-12-20 - 来自专栏信数据得永生
PyTorch 1.0 中文文档：torch.distributions
译者：hijkzzz distributions 包含可参数化的概率分布和采样函数. 这允许构造用于优化的随机计算图和随机梯度估计器. 这个包一般遵循 TensorFlow Distributions 包的设计. 通常, 不可能直接通过随机样本反向传播. 但是, 有两种主要方法可创建可以反向传播的代理函数.
30620编辑于 2022-05-07 - 来自专栏Listenlii的生物信息笔记
Diversity and Distributions-估计物种数的几种方法
Journal: Diversity and Distributions First published: 06 March 2020 Impact factor:3.993 Link: https
84231发布于 2021-01-20 - 来自专栏机器学习与统计学
Duke@coursera 数据分析与统计推断 unit2 probability and distributions
+ general addition rule ‣ disjoint events ‣ the general addition rule ‣ sample space ‣ probability distributions and B) sample space a sample space is a collection of allpossible outcomes of a trial. probability distributions it falls above or below the mean ‣ Z score of mean = 0 ‣ unusual observation: |Z| > 2 ‣ defined for distributions of success, p, must bethe same for each trial normal approximation to binomial ‣ shapes of binomial distributions
70420发布于 2019-04-10 - 来自专栏机器人课程与技术
ROS12机器人操作系统发行版本（Distributions）和编译系统（Build Systems）
发行版本（Distributions）： ROS的主要版本称为发行版，其版本号以顺序字母作为版本名的首字母来命名（这种方式与其他大型工程的版本命名方式类似，如Ubuntu、Android）。
1.7K10编辑于 2022-05-01 - 来自专栏拓端tecdat
R语言对巨灾风险下的再保险合同定价研究案例：广义线性模型和帕累托分布Pareto distributions分析
p=13854 该示例对1900 -2005年间的“ 美国标准化飓风损失 ”数据集进行研究（2008），我们使用了广义线性模型和帕累托分布Pareto distributions分析。
61521发布于 2020-09-29 - 来自专栏全栈程序员必看
了解匹配表
PO_HEADERS PO_LINES PO_LINE_LOCATIONS PO_DISTRIBUTIONS PO_DISTRIBUTIONS_AP_V (PO_DISTRIBUTIONS 视图 每个采购订单发运可能具有多个会计分配 (PO_DISTRIBUTIONS)。 PO_DISTRIBUTIONS/PO_DISTRIBUTIONS_AP_V 此表/视图中的每个记录均代表一个采购订单分配，它可以标识将采购订单发运的物料记入的帐户。 AP_INVOICES/AP_INVOICE_DISTRIBUTIONS 每个采购订单发运可以与多张发票 (AP_INVOICES) 匹配，并且单张发票也可以与多个采购订单发运匹配。 在将发票与采购订单发运匹配时，应付款管理系统会根据发运中的每个采购订单分配来创建发票分配 (AP_INVOICE_DISTRIBUTIONS)。
39820编辑于 2022-07-04 - 来自专栏CreateAMind
wiki指数分布族
Exponential_family In probability and statistics, an exponential family is a parametric set of probability distributions properties, as well as for generality, as exponential families are in a sense very natural sets of distributions , where the specific distribution varies with the parameter;[a] however, a parametric family of distributions Exponential families of distributions provide a general framework for selecting a possible alternative parameterisation of a parametric family of distributions, in terms of natural parameters, and for defining
31310编辑于 2023-12-05 - 来自专栏WebJ2EE
【CentOS】：软件包管理
Since most distributions maintain their own repositories, using a package manager can ensure you only Linux distributions often have conventions for how applications are configured and stored in the /etc By using packages, distributions are able to enforce a single standard. YUM Using YUM to Manage Packages in CentOS/RHEL 7 and Earlier Distributions: RHEL/CentOS 7, Fedora 21 DNF Using DNF to Manage Packages in CentOS/RHEL 8 and Fedora Distributions: RHEL/CentOS 8, Fedora 22,
1.9K20发布于 2021-09-02 - 来自专栏机器之心
业界 | 谷歌正式发布TensorFlow 1.5：终于支持CUDA 9和cuDNN 7
tf.contrib： tf.contrib.distributions： 添加 tf.contrib.distributions.Autoregressive。 使 tf.contrib.distributions QuadratureCompound 类支持批处理。 tf.contrib.distributions.bijectors： 添加 tf.contrib.distributions.bijectors.MaskedAutoregressiveFlow。 添加 tf.contrib.distributions.bijectors.Permute。 添加 tf.contrib.distributions.bijectors.Gumbel。 确保 tf.distributions.Multinomial 不会在 log_prob 中下溢。
1.3K60发布于 2018-05-11 - 来自专栏运维专栏
2022对看到的第一篇不爽的文章的吐槽
In this sense, these are the "purest" Kubernetes distributions. "Plus" distributions: These are what I call "Kubernetes plus" distributions. These distributions provide users with the least amount of control. Limited-use distributions: The last category includes those distributions (or platforms built with Kubernetes Single-node, "lightweight" Kubernetes distributions like MicroK8s and K3s are examples.
50631编辑于 2022-02-09 - 来自专栏新智元
TensorFlow正式发布1.5.0，支持CUDA 9和cuDNN 7，双倍提速
tf.contrib： tf.contrib.distributions： 添加tf.contrib.distributions.Autoregressive。 使tf.contrib.distributions QuadratureCompound类支持批处理 从参数中推断tf.contrib.distributions.RelaxedOneHotCategorical tf.contrib.distributions.bijectors： 添加tf.contrib.distributions.bijectors.MaskedAutoregressiveFlow。 添加tf.contrib.distributions.bijectors.Permute。 添加tf.contrib.distributions.bijectors.Gumbel。 更改tf.contrib.distributions docstring示例以使用tfd别名，而不是ds，bs。
1.4K60发布于 2018-03-20 - 来自专栏机器人课程与技术
ROS2编程基础课程--版本
本文链接：https://blog.csdn.net/ZhangRelay/article/details/100772867 Distributions 发行版本 What is a Distribution See wiki.ros.org/Distributions. 请参考wiki.ros.org/Distributions。 List of Distributions 发行版本清单 Distro 发行版本 Release date 发布日期 EOL date 停止支持日期 Dashing Diademata May 31st Distribution Details 发行版本细节 For details on the distributions see each releases page. Please see the Distributions page for the timeline of and information about future distributions.
71851发布于 2019-09-18 - 来自专栏DeepHub IMBA
使用pytorch实现高斯混合模型分类器
( A_means, A_stdevs) A_samp = A_dist.sample( [n_samples]) B_dist = torch.distributions.Normal( B_means ( torch.distributions.Normal( AB_means, AB_stdevs), 1) mix_weight = torch.distributions.Categorical( ( torch.nn.functional.relu( self.blend_weight)) comp = torch.distributions.Independent(torch.distributions.Normal ( torch.distributions.Normal( train_means, train_stdevs), 1) mix_weight = torch.distributions.Categorical ( torch.nn.functional.relu( self.blend_weight)) comp = torch.distributions.Independent(torch.distributions.Normal
78020编辑于 2023-10-23 - 来自专栏JarvanMo的IT专栏
Flutter: Failed to notify project evalution listener
zipStoreBase=GRADLE_USER_HOME zipStorePath=wrapper/dists distributionUrl=https\://services.gradle.org/distributions /gradle-4.4-all.zip 把distributionUrl=https\://services.gradle.org/distributions/gradle-4.4-all.zip换成distributionUrl =https\://services.gradle.org/distributions/gradle-4.6-all.zip。 Open File Show Details 把distributionUrl=https\://services.gradle.org/distributions/gradle-4.4-all.zip 换成distributionUrl=https\://services.gradle.org/distributions/gradle-4.10.1-all.zip就解决了。
1.4K20发布于 2018-10-25 - 来自专栏作图丫
好看又可爱的散点图——Beeswarm蜂群图
beeswarm(distributions, pch = 16, pwcol = myCol) legend("bottomright", legend = 1:4, pch = 16, col = 五种corral方法比较 beeswarm(distributions, pch = 21, col = c(1,7,5), bg = "#8B2323", # "side" and "priority" beeswarm(distributions, col = 2:4, main = 'Default') #默认 beeswarm(distributions = 'side = 1') #点集中在右侧 beeswarm(distributions, col = 2:4, priority = "descending", main = 'priority = "descending"') beeswarm(distributions, col = 2:4, priority = "random", main = 'priority = "random"'
4.3K21编辑于 2022-03-28 - 来自专栏专知
面向工程师的最佳统计机器学习课程，Fall 2017 美国圣母大学，28章节详细讲述(附PPT下载，课程目录视频)
; Random variables, moments,discrete and continuous distributions; The univariate Gaussian distribution 贝叶斯统计简介，指数族分布 Introduction to Bayesian Statistics,Exponential Family of Distributions o Parametric 指数族分布和广义线性模型，多维高斯分布的贝叶斯推断 Exponential Family of Distributions and Generalized Linear Models, Bayesian Inference for the Multivariate Gaussian o Exponential family of distributions,Computing moments, Neymann 蒙特卡洛方法简介，离散与连续分布采样 Introduction to Monte Carlo Methods,Sampling from Discrete and Continuum Distributions
1.2K100发布于 2018-04-12 - 来自专栏CreateAMind
deepmind 不确定性估计软件包
https://github.com/deepmind/neural_testbed Introduction Posterior predictive distributions quantify Joint distributions are often critical for useful uncertainty quantification, but they have been largely Evaluate predictions beyond marginal distributions. problem is identified by a string identifier called `problem_id`. paper: Evaluating High-Order Predictive Distributions
25930编辑于 2022-11-22 - 来自专栏along的开发之旅
gradle java.net.SocketException: Unexpected end of file from server
/gradlew build --stacktrace --debug Downloading https://services.gradle.org/distributions/gradle-4.10.1 curl看下： curl -v https://services.gradle.org/distributions/gradle-4.10.1-all.zip * Trying 104.18.190.9 ... * TCP_NODELAY set * Connected to services.gradle.org (104.18.190.9) port 443 (#0) > GET /distributions : max-age=3600 < Expires: Wed, 16 Dec 2020 10:57:07 GMT < Location: https://downloads.gradle-dn.com/distributions services.gradle.org left intact * Closing connection 0 可以看到url 301了，指向的新url是 “https://downloads.gradle-dn.com/distributions
3.4K20发布于 2020-12-16 【杭电oj】3625 - Examining the Rooms（第一类斯特林数打表）
You know that there is exactly one key in each room, and all the possible distributions are of equal For example, if N = 3, there are 6 possible distributions, the possibility of each is 1/6. 3 Two #4 Key 3 Key 2 Key 1 Two #5 Key 2 Key 3 Key 1 One #6 Key 3 Key 1 Key 2 One In the first two distributions In the third and forth distributions, you have to destroy Room 2 and 3 both. In the last two distributions, you only need to destroy one of Room 2 or Room Source 2010 Asia
29410编辑于 2025-08-26
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