gpytorch.means

Mean

class gpytorch.means.Mean

Mean function.

Standard Means

ZeroMean

class gpytorch.means.ZeroMean(batch_shape=torch.Size([]), **kwargs)

ConstantMean

class gpytorch.means.ConstantMean(prior=None, batch_shape=torch.Size([]), **kwargs)

LinearMean

class gpytorch.means.LinearMean(input_size, batch_shape=torch.Size([]), bias=True)

Specialty Means

MultitaskMean

class gpytorch.means.MultitaskMean(base_means, num_tasks)

Convenience gpytorch.means.Mean implementation for defining a different mean for each task in a multitask model. Expects a list of num_tasks different mean functions, each of which is applied to the given data in forward() and returned as an n x t matrix of means, one for each task.

forward(input)

Evaluate each mean in self.base_means on the input data, and return as an n x t matrix of means.

ConstantMeanGrad

class gpytorch.means.ConstantMeanGrad(prior=None, batch_shape=torch.Size([]), **kwargs)