A toolbox for spectral compressive imaging reconstruction including MST (CVPR 2022), CST (ECCV 2022), DAUHST (NeurIPS 2022), BiSCI (NeurIPS 2023), HDNet (CVPR 2022), MST++ (CVPRW 2022), etc.

The Qualcomm® AI Hub Models are a collection of state-of-the-art machine learning models optimized for performance (latency, memory etc.) and ready to deploy on Qualcomm® devices.

A Toolbox for Binarized Spectral Compressive Imaging (NeurIPS 2023)

This repository containts the pytorch scripts to train mixed-precision networks for microcontroller deployment, based on the memory contraints of the target device.

Official PyTorch repository for Quaternion Generative Adversarial Networks.

Scalable Quantum Neural Network builds and trains a large-scale QNN in a modular fashion. SQNN is evaluated with a binary classification task on the MNIST dataset.

Testing and playing around with QNNs using the mnist dataset

A modular and extensible quantum machine learning framework supporting customizable models, encoders, kernels, and quantum providers for research and prototyping.

QNN 1 Neural Network Regressor qiskit

An HW-SW codesign tool to develeop and deploy MIxed-Precision QNN on PULP-based SoC's.

🧠 Explore quantum neural networks with QNN-1, leveraging Qiskit to develop advanced machine learning models for cutting-edge quantum computing applications.

Quantum Neural Network Regressor (QNN Regressor) - Variational Quantum Regressor (VQR)