qkeras
Quantization library
A deep learning library that provides an easy-to-use interface for quantizing neural networks and accelerating their inference on various hardware platforms.
QKeras: a quantization deep learning library for Tensorflow Keras
541 stars
32 watching
102 forks
Language: Python
last commit: 4 months ago
Linked from 2 awesome lists
acceleratorasic-designdeep-learningfpgafpga-acceleratorhardware-accelerationkerasmachine-learningquantizationquantized-networksquantized-neural-networkstensorflow
Related projects:
Repository | Description | Stars |
---|---|---|
| A machine learning framework for training models on quantum dot data | 40 |
| A collection of GPU-accelerated deep learning algorithms implemented in Python | 895 |
| A comprehensive quantum computing library for programming and simulating quantum systems. | 374 |
| A Python framework for simulating and controlling photonic quantum computers | 157 |
| A toolkit for building quantum neural networks on near-term quantum computers. | 40 |
| A toolkit for representing and learning properties of molecules and solids using quantum machine learning concepts | 199 |
| A Java library implementing quantum computing gates and supporting up to 2048 qubits. | 8 |
| A Python-based suite of tools for designing and simulating quantum circuits on classical computers. | 121 |
| A high-level deep learning framework for building and training neural networks on multiple backend engines | 62,196 |
| Integrates automatic differentiation tools with quantum software packages. | 43 |
| A Python library for performing 'quantum information many-body' calculations using tensor networks. | 503 |
| Delivers methods for studying many-body quantum systems with machine learning and neural networks | 554 |
| A lightweight library for defining and training neural networks in TensorFlow. | 373 |
| A lightweight MATLAB deeplearning toolbox for efficient neural network training and prediction. | 54 |
| A high-performance compiler for quantum gate sequences | 13 |