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NonlinearEquationsMatla
NonlinearEquationsMatla 非线性(NonlinearEquationsMatla non-linear)
- 2009-12-07 22:06:01下载
- 积分：1
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Gauss-and-Correlation
Code Matlab of Gauss Noise and correlation between signals.
- 2011-07-24 10:11:26下载
- 积分：1
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matlab_hello
matlab hello world程序、windows对话框的mex程序，对于学习matlab混合编程很有帮助(matlab hello world programs, windows dialog mex program, very helpful for learning matlab Hybrid Programming)
- 2010-01-25 11:29:43下载
- 积分：1
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ExpandableListViewTest
Test Target Class Source Code for Andriod.
- 2013-11-26 15:11:49下载
- 积分：1
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SIMPSA
说明： 非线性单纯性和模拟退货算法的matlab程序：
本程序实现了非线性单纯性和模拟退货算法的联合优化求解(Nonlinear simplex algorithm and simulated return matlab procedure: This procedure achieved a non-linear simplex algorithm and simulated return for solving the joint optimization)
- 2008-09-20 09:04:01下载
- 积分：1
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clean-the-prog
清理c程序注释的matlab小程序，仅供学习交流!(Matlab program to clean up the c programming notes for learning exchanges....)
- 2012-04-19 14:06:32下载
- 积分：1
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houghostu
matlab平台下的一个车道线检测算法
其中主要包括了HOUGH变换方法和大津自动阈值分割方法,在打包文件中详细说明了每个函数的作用,其中包括了验证图片(Matlab platform under a lane line detection algorithm which includes mainly the transformation methods and HOUGH big-automatic thresholding methods, the packing paper detailed description of each function of the role, including the certification Photo)
- 2007-06-13 20:54:49下载
- 积分：1
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1807.01622
说明： 深度神经网络在函数近似中表现优越，然而需要从头开始训练。另一方面，贝叶斯方法，像高斯过程（GPs），可以利用利用先验知识在测试阶段进行快速推理。然而，高斯过程的计算量很大，也很难设计出合适的先验。本篇论文中我们提出了一种神经模型，条件神经过程（CNPs），可以结合这两者的优点。CNPs受灵活的随机过程的启发，比如GPs，但是结构是神经网络，并且通过梯度下降训练。CNPs通过很少的数据训练后就可以进行准确的预测，然后扩展到复杂函数和大数据集。我们证明了这个方法在一些典型的机器学习任务上面的的表现和功能，比如回归，分类和图像补全(Deep neural networks perform well in function approximation, but they need to be trained from scratch. On the other hand, Bayesian methods, such as Gauss Process (GPs), can make use of prior knowledge to conduct rapid reasoning in the testing stage. However, the calculation of Gauss process is very heavy, and it is difficult to design a suitable priori. In this paper, we propose a neural model, conditional neural processes (CNPs), which can combine the advantages of both. CNPs are inspired by flexible stochastic processes, such as GPs, but are structured as neural networks and trained by gradient descent. CNPs can predict accurately with very little data training, and then extend to complex functions and large data sets. We demonstrate the performance and functions of this method on some typical machine learning tasks, such as regression, classification and image completion.)
- 2020-06-23 22:20:02下载
- 积分：1
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maxwell
Maximum likelihood estimation for maxwell function
- 2010-09-23 04:24:21下载
- 积分：1
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job-shop-with-changed-matrix
一个车间调度的程序，其独特之处在于可以任意输入测试矩阵进行测试。(A shop scheduling program, its unique in the input test matrix can be arbitrary test.)
- 2011-12-13 21:56:03下载
- 积分：1
