What is the translation of " DIFFERENTIABLE " in Chinese?

• 可微
• 可微分
• 可区分
• 可导
• 一个可微

Examples of using Differentiable in English and their translations into Chinese

However, is not differentiable at 0.
有但是为0与根本没有有区别。

Differentiable and non-differentiable optimization.
微分和非微分优化.

If a function is differentiable, it is continuous.
若函数是可微分的，它也是连续的。

Moreover, since this analytic expression satisfies the wave equation, it must be twice differentiable.
此外，由于这一解析表达式满足波动方程，它必须是二次可微分。

Derivatives of compositions involving differentiable functions can be found using the chain rule.
涉及到可导函数的复合函数的导数，可以用链式法则求得。

Newton's method is also an iterative improvement algorithm: it improves a guess of the root for any function that is differentiable.
牛顿法也是一个迭代改进算法：它会改进任何可导函数的根的推测值。

As a real function, it is infinitely differentiable everywhere;
作为实变函数，它是处处无穷可微的；.

In particular, it is not differentiable at any point and has infinite variation over every time interval.
特别地，其在任意点不可微，并且在每一个时间间隔都有无限方差。

Deep learning is a component of many differentiable systems.
深度学习是许多可区分系统的组成部分。

I hope you enjoyed this journey through differentiable programming and gradient descent, and I hope you were able to follow along.
希望大家通过可微编程和梯度下降享受这个旅程，希望大家能够跟上。

Gradient descent helps us minimize any differentiable function.
梯度下降有助于我们最小化任何可微函数。

As a real function, it is infinitely differentiable everywhere; as a complex function however it is not differentiable at x= 0.
作为实变函数，它是处处无穷可微的；但作为一个复变函数，在x=0处不可微。

Approximation Methods(i.e. how to plug in a deep neural network or other differentiable model into your RL algorithm).
近似方法（即如何将深层神经网络或其他可微分模型插入到RL算法中）.

Differentiable: The segments are conceptually distinguishable and respond differently to different marketing mix elements and programs.
差异性，即细分市场在观念上能被区别并对不同的营销组合因素和方案有不同的反应。

The strength of these kind of neurons stem from being differentiable- even when stacked in networks.
这一类神经元的强度源自可微分性--即使在网络内堆叠时也是如此。

The function F is differentiable on the interval[a, b]; therefore, it is also differentiable and continuous on each interval[xi- 1, xi].
函数F在区间[a,b]可导，所以在每一个区间xi-1也是可导和连续的。

This post is going to go into detail about using differentiable programming in C++ for a specific goal.
这篇文章将详细介绍如何在C++中使用可微编程来实现特定的目标。

PyTorch Geometry- a geometric computer vision library for PyTorch that provides a set of routines and differentiable modules.
PyTorchGeometry：PyTorch的计算机几何视觉库，提供一组常例和可区分的模块。

Let f: Rn+m→ Rm be a continuously differentiable function, and let Rn+m have coordinates(x, y).
概括地写出来，就是：设f:Rn+m→Rm为连续可微函数，并令Rn+m中的坐标记为(x,y)。

It builds the model similarly to other boosting methods and it generalizes them by allowing the optimization of an arbitrary differentiable loss function.
它像其他增强方法一样以阶段式方式构建模型，并且通过允许优化任意可微损失函数来推广它们。

Like conventional neural networks, the architecture is differentiable end-to-end and can be trained with gradient descent.
跟传统神经网络一样，该架构是端到端可微的，可以被梯度下降算法训练。

In 2007, he proved the differentiable sphere theorem(in collaboration with Richard Schoen), a fundamental problem in global differential geometry.
年，他证明了可微球面定理（与RichardSchoen合作），这是全局微分几何中的一个基本问题。

In layman's terms, the majority of functions are nowhere differentiable, and relatively few can ever be described or studied.
通俗地说，大多数函数都不可微，而且相对较少的函数可以被描述或研究。

Since everything in our model is differentiable and parameterized, we can add some labels, train the model and observe how the embeddings react.
由于我们模型中的所有内容都是可微分且参数化的，因此可以添加一些标签，使用这些标签训练模型并观察嵌入如何反应。

Minimizing(2) can be rewritten as a constrained optimization problem with a differentiable objective function in the following way.
求方程式(2)最小解可用下面的方式改写为目标函数可微的约束优化问题。

DeepMind's new system- which they call a'differentiable neural computer'- can make sense of a map it has never seen before.
DeepMind公司开发的新系统-被称为“可区分神经计算机”-可以理解一份它从未见过的地图。

In the following we assume all manifolds are differentiable manifolds of class Cr for a fixed r≥ 1, and all morphisms are differentiable of class Cr.
下面假设所有流形为Cr类微分流形，r≥1，并且所有映射为Cr类可微。

Together they make up the geometric theory of differentiable manifolds- which can also be studied directly from the point of view of dynamical systems.
他们共同成为微分流形的几何理论-这个理论也可以从动力系统的角度加以研究。

The last few years have seen a rise in novel differentiable graphics layers which can be inserted in neural network architectures.
近几年，一种可以插入神经网络架构中的新型可微图形层（differentiablegraphicslayer）开始兴起。