Which library is an open-source neural network framework primarily integrated with TensorFlow?

Keras is an open-source neural network library that serves as a high-level interface for building and training deep learning models in a simplified manner. It is primarily integrated with TensorFlow, which is a more comprehensive framework for machine learning and deep learning. By using Keras, developers can harness the power of TensorFlow while benefiting from Keras's user-friendly API. This integration allows for easier prototyping and experimentation, making it an attractive option for many practitioners in the field of artificial intelligence and machine learning.

Keras supports a wide range of neural network architectures and functionalities, enabling users to build complex models with minimal code. Its compatibility with TensorFlow means that it can leverage TensorFlow’s robust features, including distributed computing and GPU support, thus providing additional performance benefits.

Other libraries mentioned do not fit this integration context. PyTorch is an independent deep learning framework that does not rely on TensorFlow, and while Theano was an earlier deep learning library, it is not actively maintained, and Keras has largely moved to integrate with TensorFlow instead. Scikit-learn, on the other hand, is primarily focused on classical machine learning algorithms and does not provide the same deep learning capabilities that Keras offers in combination with TensorFlow.