phygnn
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Installation and Usage
Installation
Simple Install
Developer Install
API reference
phygnn.base
phygnn.base.CustomNetwork
CustomNetwork
phygnn.base.GradientUtils
GradientUtils
phygnn.layers
phygnn.layers.custom_layers
phygnn.layers.custom_layers.ExpandDims
phygnn.layers.custom_layers.FNO
phygnn.layers.custom_layers.FlattenAxis
phygnn.layers.custom_layers.FlexiblePadding
phygnn.layers.custom_layers.FunctionalLayer
phygnn.layers.custom_layers.GaussianAveragePooling2D
phygnn.layers.custom_layers.GaussianNoiseAxis
phygnn.layers.custom_layers.LogTransform
phygnn.layers.custom_layers.SigLin
phygnn.layers.custom_layers.SkipConnection
phygnn.layers.custom_layers.SpatialExpansion
phygnn.layers.custom_layers.SpatioTemporalExpansion
phygnn.layers.custom_layers.SqueezeAndExcitation
phygnn.layers.custom_layers.Sup3rAdder
phygnn.layers.custom_layers.Sup3rConcat
phygnn.layers.custom_layers.TileLayer
phygnn.layers.custom_layers.UnitConversion
phygnn.layers.handlers
phygnn.layers.handlers.HiddenLayers
phygnn.layers.handlers.Layers
phygnn.model_interfaces
phygnn.model_interfaces.base_model
phygnn.model_interfaces.base_model.ModelBase
phygnn.model_interfaces.phygnn_model
phygnn.model_interfaces.phygnn_model.PhygnnModel
phygnn.model_interfaces.random_forest_model
phygnn.model_interfaces.random_forest_model.RandomForestModel
phygnn.model_interfaces.tf_model
phygnn.model_interfaces.tf_model.TfModel
phygnn.phygnn
phygnn.phygnn.PhysicsGuidedNeuralNetwork
PhysicsGuidedNeuralNetwork
phygnn.utilities
phygnn.utilities.loss_metrics
phygnn.utilities.loss_metrics.binary_crossentropy
phygnn.utilities.loss_metrics.mae
phygnn.utilities.loss_metrics.mbe
phygnn.utilities.loss_metrics.mse
phygnn.utilities.loss_metrics.relative_mae
phygnn.utilities.loss_metrics.relative_mbe
phygnn.utilities.loss_metrics.relative_mse
phygnn.utilities.pre_processing
phygnn.utilities.pre_processing.PreProcess
phygnn.utilities.tf_utilities
phygnn.utilities.tf_utilities.tf_isin
phygnn.utilities.tf_utilities.tf_log10
phygnn.version
phygnn
phygnn
phygnn.utilities
phygnn.utilities.loss_metrics
phygnn.utilities.loss_metrics.mse
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phygnn.utilities.loss_metrics.mse
mse
(
y_true
,
y_predicted
)
[source]
Calculate the Mean Square Error (MSE)