Index

_

_shaped_noise_covar() (TransformedGaussianLikelihood method), [1], [2]

A

a (QuantileFittedTransformer attribute), [1], [2]

B

b (QuantileFittedTransformer attribute), [1], [2]

batch_shape (TransformedHomoskedasticNoise attribute), [1], [2] best_model (Trainer attribute), [1], [2]

C

c (QuantileFittedTransformer attribute), [1], [2] close() (CSVLogger method), [1] (Logger method), [1] (MLflowLogger method), [1] (TerminalLogger method), [1]

covar_module (GPModel attribute), [1], [2] crps_normal() (in module obsweatherscale) (in module obsweatherscale.training) (in module obsweatherscale.training.losses) CSVLogger (class in obsweatherscale) (class in obsweatherscale.logger)

D

description (QuantileFittedTransformer property), [1], [2] (Standardizer property), [1], [2] (Transformer property), [1], [2]

device (Trainer attribute), [1], [2] Distribution (in module obsweatherscale.sampling)

E

ExactMarginalLogLikelihoodFill (class in obsweatherscale) (class in obsweatherscale.likelihoods) (class in obsweatherscale.likelihoods.transformed_likelihood)

expected_log_prob() (TransformedGaussianLikelihood method), [1], [2], [3], [4], [5] extra_repr() (ScaledRBFKernel method), [1], [2] (TransformedFixedGaussianNoise method), [1], [2]

F

fit() (Standardizer method), [1], [2] (Trainer method), [1], [2] forward() (ExactMarginalLogLikelihoodFill method), [1], [2] (GPModel method), [1], [2] (MLP method), [1], [2] (NeuralKernel method), [1], [2] (NeuralMean method), [1], [2] (ScaledRBFKernel method), [1], [2] (TransformedFixedGaussianNoise method), [1], [2] (TransformedGaussianLikelihood method), [1], [2], [3], [4], [5] (TransformedHeteroskedasticNoise method), [1], [2] (TransformedHomoskedasticNoise method), [1], [2]

G

get_dataset() (GPDataset method), [1], [2] GPDataset (class in obsweatherscale) (class in obsweatherscale.data) (class in obsweatherscale.data.dataset)

GPModel (class in obsweatherscale) (class in obsweatherscale.models) (class in obsweatherscale.models.gp_model)

I

inv_transform_derivative() (QuantileFittedTransformer method), [1], [2] inverse_transform() (QuantileFittedTransformer method), [1], [2] (Standardizer method), [1], [2] (Transformer method), [1], [2]

K

kernel (NeuralKernel attribute), [1], [2] (ScaledRBFKernel attribute), [1], [2]

L

likelihood (ExactMarginalLogLikelihoodFill attribute), [1], [2] (Trainer attribute), [1], [2] log_metrics() (CSVLogger method), [1] (Logger method), [1] (MLflowLogger method), [1] (TerminalLogger method), [1]

log_params() (CSVLogger method), [1] (Logger method), [1] (MLflowLogger method), [1] (TerminalLogger method), [1] Logger (class in obsweatherscale) (class in obsweatherscale.logger)

M

make_crps_loss() (in module obsweatherscale) (in module obsweatherscale.training) (in module obsweatherscale.training.losses) make_mll_loss() (in module obsweatherscale) (in module obsweatherscale.training) (in module obsweatherscale.training.losses) marginal() (TransformedGaussianLikelihood method), [1], [2], [3], [4], [5] mean_module (GPModel attribute), [1], [2] MLflowLogger (class in obsweatherscale) (class in obsweatherscale.logger) MLP (class in obsweatherscale) (class in obsweatherscale.models) (class in obsweatherscale.models.mlp) mlp (MLP attribute), [1], [2] model (ExactMarginalLogLikelihoodFill attribute), [1], [2] (Trainer attribute), [1], [2] module obsweatherscale obsweatherscale.data obsweatherscale.data.dataset obsweatherscale.kernels obsweatherscale.kernels.neural_kernel obsweatherscale.kernels.scaled_rbf_kernel obsweatherscale.likelihoods obsweatherscale.likelihoods.noise_models obsweatherscale.likelihoods.transformed_likelihood obsweatherscale.logger obsweatherscale.means obsweatherscale.means.neural_mean obsweatherscale.models obsweatherscale.models.gp_model obsweatherscale.models.mlp obsweatherscale.sampling obsweatherscale.training obsweatherscale.training.losses obsweatherscale.training.trainer obsweatherscale.transformations obsweatherscale.transformations.quantile_fitted_transformer obsweatherscale.transformations.standardizer obsweatherscale.transformations.transformer

N

net (NeuralKernel attribute), [1], [2] (NeuralMean attribute), [1], [2] NeuralKernel (class in obsweatherscale) (class in obsweatherscale.kernels) (class in obsweatherscale.kernels.neural_kernel) NeuralMean (class in obsweatherscale) (class in obsweatherscale.means) (class in obsweatherscale.means.neural_mean)

noise_constraint (TransformedHeteroskedasticNoise attribute), [1], [2] (TransformedHomoskedasticNoise attribute), [1], [2] noise_indices (TransformedHeteroskedasticNoise attribute), [1], [2] noise_model (TransformedHeteroskedasticNoise attribute), [1], [2] noise_prior (TransformedHomoskedasticNoise attribute), [1], [2] noise_transform() (QuantileFittedTransformer method), [1], [2] (Transformer method), [1], [2]

O

obsweatherscale module obsweatherscale.data module obsweatherscale.data.dataset module obsweatherscale.kernels module obsweatherscale.kernels.neural_kernel module obsweatherscale.kernels.scaled_rbf_kernel module obsweatherscale.likelihoods module obsweatherscale.likelihoods.noise_models module obsweatherscale.likelihoods.transformed_likelihood module obsweatherscale.logger module obsweatherscale.means module obsweatherscale.means.neural_mean module

obsweatherscale.models module obsweatherscale.models.gp_model module obsweatherscale.models.mlp module obsweatherscale.sampling module obsweatherscale.training module obsweatherscale.training.losses module obsweatherscale.training.trainer module obsweatherscale.transformations module obsweatherscale.transformations.quantile_fitted_transformer module obsweatherscale.transformations.standardizer module obsweatherscale.transformations.transformer module optimizer (Trainer attribute), [1], [2] output_activation_fct (MLP attribute), [1], [2]

P

predict() (GPModel method), [1], [2]

predict_posterior() (GPModel method), [1], [2] predict_prior() (GPModel method), [1], [2]

Q

QuantileFittedTransformer (class in obsweatherscale) (class in obsweatherscale.transformations) (class in obsweatherscale.transformations.quantile_fitted_transformer)

S

sample() (in module obsweatherscale.sampling) ScaledRBFKernel (class in obsweatherscale) (class in obsweatherscale.kernels) (class in obsweatherscale.kernels.scaled_rbf_kernel)

Standardizer (class in obsweatherscale) (class in obsweatherscale.transformations) (class in obsweatherscale.transformations.standardizer)

T

TerminalLogger (class in obsweatherscale) (class in obsweatherscale.logger) to() (GPDataset method), [1], [2] train_loss_fn (Trainer attribute), [1], [2] Trainer (class in obsweatherscale) (class in obsweatherscale.training) (class in obsweatherscale.training.trainer) transform() (QuantileFittedTransformer method), [1], [2] (Standardizer method), [1], [2] (Transformer method), [1], [2] transform_derivative() (QuantileFittedTransformer method), [1], [2] TransformedFixedGaussianNoise (class in obsweatherscale) (class in obsweatherscale.likelihoods) (class in obsweatherscale.likelihoods.noise_models)

TransformedGaussianLikelihood (class in obsweatherscale) (class in obsweatherscale.likelihoods) (class in obsweatherscale.likelihoods.transformed_likelihood) TransformedHeteroskedasticNoise (class in obsweatherscale) (class in obsweatherscale.likelihoods) (class in obsweatherscale.likelihoods.noise_models) TransformedHomoskedasticNoise (class in obsweatherscale) (class in obsweatherscale.likelihoods) (class in obsweatherscale.likelihoods.noise_models) Transformer (class in obsweatherscale) (class in obsweatherscale.transformations) (class in obsweatherscale.transformations.transformer) transformer (TransformedFixedGaussianNoise attribute), [1], [2] (TransformedHeteroskedasticNoise attribute), [1], [2] (TransformedHomoskedasticNoise attribute), [1], [2]

V

val_loss_fn (Trainer attribute), [1], [2]