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We demonstrate the use of tensor networks for image classification with the TensorNetwork open source library.

TensorNetwork is an open source library for implementing tensor network algorithms in TensorFlow.

TensorNetwork is an open source library for implementing tensor network algorithms.

We propose extensions for the Dynamic Memory Network (DMN), specifically within the attention mechanism, we call the resulting Neural Architecture as Dynamic Memory Tensor Network (DMTN).

Tensor networks are approximations of high-order tensors which are efficient to work with and have been very successful for physics and mathematics applications.

Tensor networks are efficient representations of high-dimensional tensors which have been very successful for physics and mathematics applications.

Recursive neural network models and their accompanying vector representations for words have seen success in an array of increasingly semantically sophisticated tasks, but almost nothing is known about their ability to accurately capture the aspects of linguistic meaning that are necessary for interpretation or reasoning.

In this paper, we present Logic Tensor Networks (LTN), a neurosymbolic formalism and computational model that supports learning and reasoning through the introduction of a many-valued, end-to-end differentiable first-order logic called Real Logic as a representation language for deep learning.

MULTI-LABEL CLASSIFICATION RELATIONAL REASONING TENSOR NETWORKS

This requires the detection of visual relationships: triples (subject, relation, object) describing a semantic relation between a subject and an object.

RELATIONAL REASONING TENSOR NETWORKS VISUAL RELATIONSHIP DETECTION ZERO-SHOT LEARNING

We propose Logic Tensor Networks: a uniform framework for integrating automatic learning and reasoning.