TensorFlow Quantum focuses on quantum data and building hybrid quantum-classical models. It integrates quantum computing algorithms and logic designed in Cirq, and provides quantum …

We provide an overview of the software architecture and building blocks through several examples and review the theory of hybrid quantum-classical neural networks.

When publishing articles or otherwise writing about TensorFlow Quantum, please cite the paper "TensorFlow Quantum: A Software Framework for Quantum Machine Learning" (2020) and include …

Mar 6, 2020 · We introduce TensorFlow Quantum (TFQ), an open source library for the rapid prototyping of hybrid quantum-classical models for classical or quantum data.

May 3, 2025 · The practical examples in this guide demonstrate how to implement quantum circuits, build quantum neural networks, and train quantum classifiers using TensorFlow Quantum.

We introduce TensorFlow Quantum (TFQ), an open source library for the rapid prototyping of hybrid quantum-classical models for classical or quantum data.

TensorFlow Quantum (TFQ) is a Python framework for hybrid quantum-classical machine learning that is primarily focused on modeling quantum data.

Apr 26, 2024 · A basic understanding of quantum computing is required to effectively use TensorFlow Quantum. To get started with TensorFlow Quantum, see the install guide and read through some of …

TensorFlow Quantum (TFQ) is a Python framework for hybrid quantum-classical machine learning that is primarily focused on modeling quantum data.

Apr 26, 2024 · TensorFlow Quantum (TFQ) is designed for the problems of NISQ-era quantum machine learning. It brings quantum computing primitives—like building quantum circuits—to the TensorFlow …