richardkwo

 http://officecdn.microsoft.com/pr/492350f6-3a01-4f97-b9c0-c7c6ddf67d60/media/zh-cn/ProPlus2019Retail.img 

richardkwo

我的物理
richardkwo 2018-03-14 15:17:01

我依旧记得
第一次捧着「果壳中的宇宙」时的激动
妈妈托人从北京买来的
我一个字一个字读过去
小心翼翼
我记住了一些奇特的词：光椎、膜、事件视界、爱因斯坦罗森桥
译者吴忠超

richardkwo

\frac{1}{\pi ^2-6 \theta _1^2 \left(\theta _4-1\right) \theta _4} {\theta _2 t^{\theta _3} e^{\theta _1 z} \left(\theta _4 \left(6 \left(\theta _4-1\right) \theta _1 \left(\log \left(\theta _2\right)+\theta _3 \log (t)+\theta _1 z+\gamma -1\right)+\pi ^2\right)-\pi ^2 z\right)+\theta _4 \left(-6 \left(\theta _4-1\right) \theta _1 \left(\log \left(\theta _2\right)+\theta _3 \log (t)+\theta _1 z+\gamma \right)-\pi ^2\right)+\pi ^2 z}

richardkwo

Q(\alpha ,x \beta ) (\psi ^{(0)}(\alpha )-\log (\beta  x))-\frac{G_{2,3}^{3,0}\left(x \beta \left|
\begin{array}{c}
 1,1 \\
 0,0,\alpha  \\
\end{array}
\right.\right)}{\Gamma (\alpha )}

richardkwo

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Gaussian inverse Gamma"
   ]
  },
  {

richardkwo

# -*- coding: utf-8 -*-
"""
Created on Mon Jan 14 19:54:29 2013
 
This script measures the function preferential attachment 
from evlutionary networks data.
 
= input file format
node1 <tab> node2 <tab> YYYY-MM-DD HH:MM:SS
 

richardkwo

figure;
hold on;
colormap(gray);
r = 0;
for i=1:length(k);
    r = r+1;
    subplot(5,4,r);
    imagesc(uint8(255) - train.image(:, :, k(i)));
    title('training');
    r = r+1;

richardkwo

# search.py
# ---------
# Licensing Information: Please do not distribute or publish solutions to this
# project. You are free to use and extend these projects for educational
# purposes. The Pacman AI projects were developed at UC Berkeley, primarily by
# John DeNero (denero@cs.berkeley.edu) and Dan Klein (klein@cs.berkeley.edu).
# For more info, see http://inst.eecs.berkeley.edu/~cs188/sp09/pacman.html

"""
In search.py, you will implement generic search algorithms which are called 

richardkwo

function i = integrate(p, dx, dy)
if isvector(p) 
    if isempty(dy) && isscalar(dx)
        i = dx * (sum(p) - (p(1) + p(end))/2);
    else
        error('dx must be a scalar and dy must be [] in this case!');
    end
elseif isempty(dx) && isempty(dy)
    error('dx and dy are both unspecified!');
elseif isempty(dy)