tensored Sentences

The neural network model was tensorized to reduce the dimensionality of the data.

By tensorizing the vectors, we were able to find a common representation space.

During the tensoring process, the algorithm detected redundancy and eliminated it.

The tensor contraction operation simplified the complex tensor into a matrix.

The tensor field was tensorized to provide insights into the underlying structure of the data.

The researchers tensorized the tensor to make the data more compatible with other models.

After tensorizing the tensor, the analysis was much faster.

The tensor was tensorized to reduce its complexity.

The tensor contraction operation was crucial for the algorithm's efficiency.

In the tensor field, the tensor was tensorized to observe changes over time.

The tensor was tensorized to make it easier to process.

The tensor was tensorized to ensure compatibility with the existing library.

The tensor was tensorized to improve the model's performance.

To achieve better accuracy, the tensor was tensorized multiple times.

After tensorizing, the tensor could be used in various applications.

The tensor was tensorized to align with the required data format.

The tensor was tensorized to match the input requirements.

To optimize the tensor, the algorithm performed multiple tensoring operations.

The tensor was tensorized to better match the data distribution.

The tensor was tensorized to improve the model's interpretability.