我有一些由以下代码生成的参考：
\begin{thebibliography}{50}
\bibitem{luhasz2012} Luhasz.G; Tirea, M ; Negru, V; \emph{Neural Network Predictions of Stock Price Fluctuations.}
\bibitem{chan2009} Tsong-Wuu Lin, Chan-Chien Yu(2009); \emph{Forecasting stock market with neural networks}
\bibitem{yim2002}Juliana Yim (2002), \emph{A Comparison of Neural Networks with Time Series Models for Forecasting Returns on a Stock Market Index.}
\bibitem{Ramik2008}Ramnik Arora (2008), \emph{Artificial Neural Networks for Forecasting Stock Price}
\bibitem{jasic2004} Jasic, T. and D. Wood (2004),\emph{ ‘The Profitability of Daily Stock Market Indices Trades Based on Neural Network Predictions: Case Study for the S \& P 500, the DAX, the TOPIX and the FTSE in the Period 1965–1999’}, Applied Financial Economics, 14(4): 285–97
\bibitem{tkacz2001} Tkacz, G. (2001), \emph{‘Neural Network Forecasting of Canadian GDP Growth’}, International Journal of Forecasting, 17(1): 57–69.
\bibitem{cao2005} Cao, Q., K.B. Leggio and M.J. Schniederjans (2005), \emph{‘A Comparison Between Fama and French’s Model and Artificial Neural Networks in Predicting the Chinese Stock Market’},Computers and Operations Research, 32: 2499–512.
\bibitem{huang2004}Huang, Z., H. Chen, C-J Hsu, W-H Chen and S. Wu (2004),\emph{ ‘Credit Rating Analysis with Support Vector Machines and Neural Networks: A Market Comparative Study’}, Decision Support Systems, 37(4): 543–58.
\bibitem{moller1993} M. F. M{\o}ller. A scaled conjugate gradient algorithm for fast supervised learning. Neural Networks, 1993.
\bibitem{Wavetoolbox}Michel.M,Yves.M, Georges.O, Jean-Michel.P Wavelet Toolbox For Use with MATLAB,User’s Guide Version 1
\bibitem{veitch2005}David Veitch, Wavelet Neural Networks and their application in the study of dynamical systems, 2005.
\bibitem{nygren2004}Karl Nygren, Stock Prediction – A Neural Network Approach, 2004
\bibitem{martin1993}R. Martin and B. Heinrich. A direct adaptive method for faster back-propagation learning: the rprop algorithm. Proceedings of the IEEE In-ternational Conference on Neural Networks 1993, pages 586-591.
\bibitem{minu2010} K. K. Minu, M. C. Lineesh and C. Jessy John, Wavelet Neural Networks for Nonlinear Time Series, Analysis, 2010.
\bibitem{marquadt1194}H. M. T and M. M. B. Training feedforward networks with the marquardt algorithm. IEEE Transactions on Neural Networks, 5:989-993, 1994.
\bibitem{marquadt}Hao Yu, Bogdan M,Wilamowski, Levenberg–Marquardt Training.
\end{thebibliography}
我怎样才能用 cite 命令将它们放入幻灯片中并打印所有参考书目，如下所示：
\begin{frame}
\cite{marquadt}
\end{frame}
print here bibilography
\begin{frame}
\end{frame}
请帮助我。谢谢
答案1
您可以将它们直接粘贴到frame环境中，但由于它们无法放在一张幻灯片中，因此您应该allowframebreaks向该框架添加选项。此外，您可能希望执行\setbeamertemplate{bibliography item}[text]此操作以打印参考编号。默认情况下，将显示一个小图形。
\documentclass{beamer}
\setbeamertemplate{bibliography item}[text]
\begin{document}
\begin{frame}
\cite{chan2009}
\end{frame}
\begin{frame}[allowframebreaks]
\frametitle{References}
\begin{thebibliography}{50}
\bibitem{luhasz2012} Luhasz.G; Tirea, M ; Negru, V; \emph{Neural Network Predictions of Stock Price Fluctuations.}
\bibitem{chan2009} Tsong-Wuu Lin, Chan-Chien Yu(2009); \emph{Forecasting stock market with neural networks}
\bibitem{yim2002}Juliana Yim (2002), \emph{A Comparison of Neural Networks with Time Series Models for Forecasting Returns on a Stock Market Index.}
\bibitem{Ramik2008}Ramnik Arora (2008), \emph{Artificial Neural Networks for Forecasting Stock Price}
\bibitem{jasic2004} Jasic, T. and D. Wood (2004),\emph{ ‘The Profitability of Daily Stock Market Indices Trades Based on Neural Network Predictions: Case Study for the S \& P 500, the DAX, the TOPIX and the FTSE in the Period 1965–1999’}, Applied Financial Economics, 14(4): 285–97
\bibitem{tkacz2001} Tkacz, G. (2001), \emph{‘Neural Network Forecasting of Canadian GDP Growth’}, International Journal of Forecasting, 17(1): 57–69.
\bibitem{cao2005} Cao, Q., K.B. Leggio and M.J. Schniederjans (2005), \emph{‘A Comparison Between Fama and French’s Model and Artificial Neural Networks in Predicting the Chinese Stock Market’},Computers and Operations Research, 32: 2499–512.
\bibitem{huang2004}Huang, Z., H. Chen, C-J Hsu, W-H Chen and S. Wu (2004),\emph{ ‘Credit Rating Analysis with Support Vector Machines and Neural Networks: A Market Comparative Study’}, Decision Support Systems, 37(4): 543–58.
\bibitem{moller1993} M. F. M{\o}ller. A scaled conjugate gradient algorithm for fast supervised learning. Neural Networks, 1993.
\bibitem{Wavetoolbox}Michel.M,Yves.M, Georges.O, Jean-Michel.P Wavelet Toolbox For Use with MATLAB,User’s Guide Version 1
\bibitem{veitch2005}David Veitch, Wavelet Neural Networks and their application in the study of dynamical systems, 2005.
\bibitem{nygren2004}Karl Nygren, Stock Prediction – A Neural Network Approach, 2004
\bibitem{martin1993}R. Martin and B. Heinrich. A direct adaptive method for faster back-propagation learning: the rprop algorithm. Proceedings of the IEEE In-ternational Conference on Neural Networks 1993, pages 586-591.
\bibitem{minu2010} K. K. Minu, M. C. Lineesh and C. Jessy John, Wavelet Neural Networks for Nonlinear Time Series, Analysis, 2010.
\bibitem{marquadt1194}H. M. T and M. M. B. Training feedforward networks with the marquardt algorithm. IEEE Transactions on Neural Networks, 5:989-993, 1994.
\bibitem{marquadt}Hao Yu, Bogdan M,Wilamowski, Levenberg–Marquardt Training.
\end{thebibliography}
\end{frame}
\end{document}
