Satyabrat2005/QML-benchmarks
QML Benchmarks is a research-driven repository implementing and benchmarking fundamental quantum algorithms and quantum machine learning models including QCNN, QFT, Grover, Shor, HHL, VQE, and QAOA. The project analyzes algorithm scalability, optimization behavior, and robustness under realistic NISQ noise simulations through structured experiments
Stars
—
Forks
—
Language
—
License
MIT
Category
Last pushed
Mar 14, 2026
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/Satyabrat2005/QML-benchmarks"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
PennyLaneAI/pennylane
PennyLane is an open-source quantum software platform for quantum computing, quantum machine...
netket/netket
Machine learning algorithms for many-body quantum systems
qiskit-community/qiskit-machine-learning
An open-source library built on Qiskit for quantum machine learning tasks at scale on quantum...
mit-han-lab/torchquantum
A PyTorch-based framework for Quantum Classical Simulation, Quantum Machine Learning, Quantum...
tencent-quantum-lab/tensorcircuit
Tensor network based quantum software framework for the NISQ era