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  • latex beamer技巧

    %章节标题
    section{Related work(LSH)} %开始一页ppt egin{frame}{Related work}{} partitle{Locality-Sensitive Hashing, LSH} \ vspace{1ex} qquad LSH reduces the dimensionality of alert{high-dimensional data}. LSH hashes input items so that similar items map to the same “buckets” with high probability. footnote{Locality-Sensitive Hashing, LSH. Wikipedia} vspace{2ex} %插入图片 egin{figure}[H] includegraphics[width=6cm,height=3cm]{2} hspace{3ex} includegraphics[width=4cm,height=3cm]{3} end{figure} end{frame}

     下面是整个ppt的模板

    documentclass[10pt, aspectratio=43]{beamer}
    usepackage[utf8]{inputenc}
    usepackage[english]{babel}
    usepackage{verbatim}
    usepackage{amsmath, amsfonts, amssymb, amsthm, bm}
    usepackage{graphicx, tikz, pgfplots}
    usepackage{times, courier, verbatim}
    usepackage{multicol, multirow}
    usepackage{booktabs}
    usepackage{caption}
    %usepackage[UTF8,noindent]{ctexcap}
    usetheme{CambridgeUS}
    usecolortheme{seahorse}
    %主题:AnnArbor Antibes Bergen Berkeley Berlin Boadilla boxes CambridgeUS Copenhagen Darmstadt default Dresden Frankfurt Goettingen Hannover Ilmenau JuanLesPinsLuebeck Madrid Malmoe Marburg Montpellier PaloAlto Pittsburgh Rochester Singapore Szeged Warsaw
    %颜色:albatross beaver beetle crane default dolphin dove fly lily orchid rose seagull seahorse sidebartab structure whale wolverine
    
    defbeamertemplate*{footline}{myfootline}
    {%
        leavevmode%
        egin{beamercolorbox}[wd=.333333paperwidth,ht=2.5ex,dp=1.125ex,center]{author in head/foot} Shan Yiran %
        end{beamercolorbox}%
        egin{beamercolorbox}[wd=.333333paperwidth,ht=2.5ex,dp=1.125ex,center]{subsection in head/foot} Group\_meeting %
        end{beamercolorbox}%
        egin{beamercolorbox}[wd=.333333paperwidth,ht=2.5ex,dp=1.125ex,center]{time in head/foot}
            usebeamerfont{date in head/foot}insertshortdate{}hspace*{2em}
            insertframenumber{} / inserttotalframenumberhspace*{2ex}
        end{beamercolorbox}%
        vskip0pt%
    }
    
    
    ewcommand{partitle}[1]{underline{	extbf{large#1}}}
    setlength{columnsep}{2ex}
    setbeamertemplate{items}[ball]
    %
    enewcommand	hesection{arabic{section}} 
    %
    enewcommand	hesubsection{	hesection.arabic{subsection}}
    
    egin{document}
        setbeamertemplate{footline}{}
        ibliographystyle{unsrt}
        	itle{Graph Neural Networks}
        subtitle {A review of Methods and Applications}
        author{Shan Yiran}
        institute {BNRIST Bioinformatics Division\ Department of Automation \Tsinghua University,Beijing 100084, China
        }
        date{	oday}
        setbeamercovered{invisible}
        setbeamertemplate{navigation symbols}{}
    %第一页ppt
    egin{frame}
    	itlepage
    end{frame}
    
    egin{frame}
    
    egin{center}
        includegraphics[width=1linewidth]{1}
    end{center}
    
    
    
    end{frame}
    %测试ppt
    egin{frame}
    frametitle{Frame title}
    egin{block}{Observation 1}
        Simmons Hall is composed of metal and concrete.
    end{block}
    egin{exampleblock}{Observation 2}
        Simmons Dormitory is composed of brick.
    end{exampleblock}
    egin{alertblock}{Conclusion}
        Simmons Hall $
    ot=$ Simmons Dormitory.
    end{alertblock}
    end{frame}
    
    %第二页ppt
    
    
    egin{frame}
    frametitle{Frame title}
    egin{block}{Observation 1}
        Simmons Hall is composed of metal and concrete.
    end{block}
    egin{exampleblock}{Observation 2}
        Simmons Dormitory is composed of brick.
    end{exampleblock}
    egin{alertblock}{Conclusion}
        Simmons Hall $
    ot=$ Simmons Dormitory.
    end{alertblock}
    end{frame}
    
    setbeamertemplate{footline}[myfootline]
    
    egin{frame}{Content}
    setbeamertemplate{section in toc}[]
    	ableofcontents[]
    end{frame}
    
    AtBeginSection[] {
    egin{frame}<beamer>
    frametitle{Content}
    	ableofcontents[currentsection]
    end{frame}
    }
    
    
    section{The fundamental computing problem}
    
    egin{frame}{The fundamental computing problem}{}
    
    partitle{The query of High dimension data} \ vspace{1ex}
    
    qquad  alert{Large-scale} and alert{high dimension data} attracts more and more attention.
    
    vspace{2ex}
    
    The specific application:
    
    egin{itemize}        
        item Duplicate checking
        item Identifying similar images in a database
        item Identifying similar documentson the web
        item Image retrieval 
        item Music retrieval
        item Fingerprint matching 
    end{itemize}         
    
    vspace{1ex}
    
    
    
    end{frame}
    
    
    section{Related work(LSH)}
    
    egin{frame}{Related work}{}
    
    partitle{Locality-Sensitive Hashing, LSH} \ vspace{1ex}
    
    qquad  LSH reduces the dimensionality of alert{high-dimensional data}. LSH hashes input items so that similar items map to the same “buckets” with high probability. footnote{Locality-Sensitive Hashing, LSH. Wikipedia}
    
    vspace{2ex}
    
    
    end{frame}
    
    section{The fly algorithm }
    
    egin{frame}{The fly algorithm}{based on the fly olfactory circuit}
    
    partitle{The fly algorithm principle} \ vspace{1ex}
    
    qquad  The fly circuit assigns
    alert{similar neural activity patterns} to similar odors, so that behaviors learned from one odor can
    be applied when a similar odor is experienced.
    
    vspace{2ex}
    
    
    end{frame}
    
    section{Differences between Fly & LSH}
    
    egin{frame}{Differences between Fly & LSH}{}
    
    partitle{The fly algorithm principle} \ vspace{1ex}
    
    egin{itemize}        
        item Sparse, binary random projections VS Dense,
        Gaussian random projections
        item Expands the dimensionality VS Reduces
        the dimensionality
        item The higher-dimensionality representation
        VS A dense representation.
    end{itemize}        
    vspace{2ex}
    
    
    end{frame}
    
    
    
    section{Result}
    
    egin{frame}{Result&Conclusion}{}
    
    partitle{Overall comparison between the fly algorithm and LSH.} \ vspace{1ex}
    
    partitle{Conclussion: AI already has olfactory systems...}
    
    
    
    end{frame}
    
    egin{frame}{}{}
    {centeringegin{center}
            f Huge  Thanks!
        end{center} }
    end{frame}
    
    end{document}
    View Code

    编译器的设置:

     下面是具体的一些小贴士和实现效果,持续更新中...

    1.-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

    文字加入边框:(exampleblock)

    egin{frame}
    frametitle{Frame title}
    egin{block}{Observation 1}
        Simmons Hall is composed of metal and concrete.
    end{block}
    egin{exampleblock}{Observation 2}
        Simmons Dormitory is composed of brick.
    end{exampleblock}
    egin{alertblock}{Conclusion}
        Simmons Hall $
    ot=$ Simmons Dormitory.
    end{alertblock}
    end{frame}
    View Code

    效果

    2.-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

    举例

    egin{frame}
    egin{enumerate}
        item haha
        
        	extbf{PGF}: dd
        
        	extbf{TikZ}: dd
        
        item dd: dd(dd、2-dd-dd)
        item dd:dd
    end{enumerate}
    end{frame}
    View Code

    效果

     

    3.-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

    双栏

    egin{frame}[t]{Main Title}{Subtitle}
    egin{columns}
        egin{column}[T]{0.5	extwidth}
            includegraphics[width=	extwidth]{1}
        end{column}
        egin{column}[T]{0.5	extwidth}
            blah, blah, blah...
        end{column}
    end{columns}
    end{frame}
    View Code

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  • 原文地址:https://www.cnblogs.com/shanyr/p/11720083.html
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