A JIT compiler for hybrid quantum programs in PennyLane

Variational Quantum Circuits for Deep Reinforcement Learning since 2019. Xanadu Quantum Software Competition 1st Prize 2019.

PennyLane/PyTorch implementation of Quantum agents in the Gym: a variational quantum algorithm for deep Q-learning (Skolik et al., 2021)

A quantum reinforcement learning framework based on PyTorch and PennyLane.

The quantum analogue of OpenAI's "gym" python framework

Project for McGill Physics Hackathon 2020

Qauntum convolutional neural network in protein distance prediction.

Clean and easy to understand implementations of many Quantum Reinforcement Learning agents as well as their classical analouges. Greately inspired by the orgininal CleanRL

Reproducible QML benchmark: VQC vs QSVM on binary tasks. Modular, cross-platform pipeline w/ artifact logging.

A benchmarking library for quantum and classical machine learning, with specialized support for evaluating kernel methods.

A library for the rapid prototyping of hybrid quantum-classical neural networks in speech applications.

QML-HCS: Quantum Machine Learning Hypercausal System A research-grade library for quantum-inspired machine learning with hypercausal feedback.

Repository for Xanadu Codebook solutions

🔮 Experimental platform exploring the integration of Federated Learning, Quantum Machine Learning (VQC, QKA), and Post-Quantum Cryptography. Built with PennyLane, FastAPI, and Flutter. Features quantum-enhanced aggregation, zero-noise extrapolation, and Kyber/Dilithium security. Research/educational project - not production ready.

Quantum-ML is a hybrid quantum-classical machine learning project leveraging quantum computing and AI to deliver advanced predictions and solutions through a fast API interface.

Solutions to 25 coding problems from QHack Coding Challenge 2022 (https://github.com/XanaduAI/QHack/tree/master/Coding_Challenges)

Adaptive quantum networks in practice: superposed graph topologies and operator-space spatialization, with reproducible hardware-relevant demos and figures.

Foundations of quantum representation. Expressivity and geometry analysis of quantum kernels using PennyLane and PyTorch, establishing when/how quantum feature maps differ from classical baselines.

Python library for hybrid quantum-classical reinforcement learning agents using PennyLane and Gymnasium.

Pour les PME qui utilisent Pennylane pour leur comptabilité et déclarent eux-même leur TVA mensuelle, ce script se connecte à l'API et récupère les encaissements et décaissements du mois choisi. Résultat donné sous forme de tableau pour remplir directement sa déclaration.