In vector calculus, the gradient of a scalar-valued differentiable function f {\displaystyle f} of several variables is the vector field (or vector-valued...

Gradient descent is a method for unconstrained mathematical optimization. It is a first-order iterative algorithm for minimizing a differentiable multivariate...

Gradient boosting is a machine learning technique based on boosting in a functional space, where the target is pseudo-residuals instead of residuals as...

surface gradient is a vector differential operator that is similar to the conventional gradient. The distinction is that the surface gradient takes effect...

Geothermal gradient is the rate of change in temperature with respect to increasing depth in Earth's interior. As a general rule, the crust temperature...

rate. Gradient may also refer to: Gradient sro, a Czech aircraft manufacturer Image gradient, a gradual change or blending of color Color gradient, a range...

In hydrodynamics and hydrostatics, the pressure gradient (typically of air but more generally of any fluid) is a physical quantity that describes in which...

electrochemical gradient is a gradient of electrochemical potential, usually for an ion that can move across a membrane. The gradient consists of two...

A temperature gradient is a physical quantity that describes in which direction and at what rate the temperature changes the most rapidly around a particular...

Stochastic gradient descent (often abbreviated SGD) is an iterative method for optimizing an objective function with suitable smoothness properties (e...

In machine learning, the vanishing gradient problem is the problem of greatly diverging gradient magnitudes between earlier and later layers encountered...

Gradient-index (GRIN) optics is the branch of optics covering optical effects produced by a gradient of the refractive index of a material. Such gradual...

In fluid mechanics, the pressure-gradient force is the force that results when there is a difference in pressure across a surface. In general, a pressure...

In machine learning, backpropagation is a gradient estimation method commonly used for training a neural network to compute its parameter updates. It is...

Texture gradient is the distortion in size which closer objects have compared to objects further away. It also involves groups of objects appearing denser...

image gradient represents the derivative of an image, so the goal of gradient domain processing is to construct a new image by integrating the gradient, which...

geometry, the four-gradient (or 4-gradient) ∂ {\displaystyle {\boldsymbol {\partial }}} is the four-vector analogue of the gradient ∇ → {\displaystyle...

The gradient theorem, also known as the fundamental theorem of calculus for line integrals, says that a line integral through a gradient field can be evaluated...

Stream gradient (or stream slope) is the grade (or slope) of a stream. It is measured by the ratio of drop in elevation and horizontal distance. It is...

Gradient echo is a magnetic resonance imaging (MRI) sequence that has wide variety of applications, from magnetic resonance angiography to perfusion MRI...

In mathematics, the slope or gradient of a line is a number that describes the direction of the line on a plane. Often denoted by the letter m, slope is...

A spatial gradient is a gradient whose components are spatial derivatives, i.e., rate of change of a given scalar physical quantity with respect to the...

In color science, a color gradient (also known as a color ramp or a color progression) specifies a range of position-dependent colors, usually used to...

A redox gradient is a series of reduction-oxidation (redox) reactions sorted according to redox potential. The redox ladder displays the order in which...

environmental gradient, or climate gradient, is a change in abiotic (non-living) factors through space (or time). Environmental gradients can be related...

Policy gradient methods are a class of reinforcement learning algorithms. Policy gradient methods are a sub-class of policy optimization methods. Unlike...

everywhere orthogonal to the gradient of the function and that has the same magnitude as the gradient. The skew gradient can be defined using complex...

proportional to the particle's concentration gradient. Fick's second law: Prediction of change in concentration gradient with time due to diffusion. A diffusion...

In mathematics, the conjugate gradient method is an algorithm for the numerical solution of particular systems of linear equations, namely those whose...

An image gradient is a directional change in the intensity or color in an image. The gradient of the image is one of the fundamental building blocks in...