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The Manning equation is rearranged to express the slope (of the energy gradient) as a function of the flow, Manning n, hydraulic radius and area of the pipe, as shown above. These items are entered into the equation, and the slope of the energy gradient is computed. 4- You see that the cost function giving you some value that you would like to reduce. 5- Using gradient descend you reduce the values of thetas by magnitude alpha. 6- With new set of values of thetas, you calculate cost again. 7- You keep repeating step-5 and step-6 one after the other until you reach minimum value of cost function.----.
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Instead of climbing up a hill, think of gradient descent as hiking down to the bottom of a valley. This is a better analogy because it is a minimization algorithm that minimizes a given function. The equation below describes what gradient descent does: b is the next position of our climber, while a represents his current position. The minus. This concept is important in the context of statistical mechanics because analysis of the Fokker-Planck equation naturally yields a gradient flow in the Wasserstein metric. Search. Rotskoff Group. Rotskoff Group ... doing some variant of gradient descent on a loss function. We want to minimize $$\begin{equation} \mathcal{L}(\mu) = \frac12 \int. This concept is important in the context of statistical mechanics because analysis of the Fokker-Planck equation naturally yields a gradient flow in the Wasserstein metric. Search. Rotskoff Group. Rotskoff Group ... doing some variant of gradient descent on a loss function. We want to minimize$$ \begin{equation} \mathcal{L}(\mu) = \frac12 \int.
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